May 2025: Top 20 Must-Know Claude MCP Servers

Model Context Protocol (MCP servers claude) works like a digital USB-C port for AI applications. It standardizes how programs feed context to Large Language Models.

This open protocol changes how Claude connects with external tools and data sources, pushing its abilities far beyond simple conversations.

Think of how your smartphone connects to different accessories – MCP servers create the same seamless connection between Claude and diverse tools and information sources.

The MCP ecosystem grows daily, with developers building specialized servers for specific needs. The Sequential Thinking MCP server helps Claude tackle complex tasks through structured thinking processes.

Meanwhile, Atlassian’s Remote MCP Server lets teams summarize work and create issues without compromising enterprise-level security.

MCP servers don’t need special hosting requirements – they work virtually anywhere. New platforms like the Cline MCP Marketplace show the protocol’s rising popularity. This standardized approach creates better connections between AI systems and various data sources, building a more capable AI environment.

Filesystem MCP Server

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The Filesystem MCP Server gives Claude secure access to local files and directories. It enables reading, writing, and managing files through standard protocols. This foundational tool takes Claude beyond conversation and into practical file operations.

Filesystem MCP Server functionality

The Filesystem MCP Server lets Claude work with files securely and efficiently. Core functions include reading file contents, creating new files, updating existing files with pattern matching, listing directory contents, creating directories, and managing file structures. Advanced features go further with targeted text replacements within files, session-aware path management, and strong security measures that prevent directory traversal attacks.

Filesystem MCP Server setup

Setting up the Filesystem MCP Server takes just a few steps:

1. Install Claude Desktop (or compatible MCP client)

2. Install Node.js (if using the TypeScript implementation)

3. Edit the Claude configuration file:

   • For macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

   • For Windows: %APPDATA%Claudeclaude_desktop_config.json

4. Add the server configuration with permitted directories:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/directory1", "/path/to/directory2"]
    }
  }
}

5. Restart Claude Desktop to apply changes

Filesystem MCP Server use cases

We help you unlock numerous practical applications with this server. Developers can ask Claude to review codebases, suggest improvements, and write new code directly to files. Researchers benefit from streamlined data workflows where Claude reads, processes, and saves results. The server also creates better learning experiences by allowing Claude to create example code files and save explanations for future reference.

Filesystem MCP Server integration with Claude

After successful integration, Claude shows available tools like read_file, write_file, and list_directory in its interface. You can instruct Claude to work with files using natural language rather than complex commands. Watch for the hammer icon in Claude Desktop’s interface – it indicates active MCP tools. Claude can now maintain context across conversations by referencing previously created files.

Filesystem MCP Server compatibility

The server works with multiple Claude interfaces, primarily Claude Desktop. You’ll find alternative implementations in both TypeScript and Python with similar capabilities. The server also integrates with VSCode and Cline extensions for direct IDE connections.

Filesystem MCP Server repository

Multiple implementations exist with different feature sets. Notable options include official Anthropic references and community implementations like @modelcontextprotocol/server-filesystem. Enhanced versions such as @safurrier/mcp-filesystem offer advanced features like smart context management and token-efficient operations for handling large files.

PostgreSQL MCP Server

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PostgreSQL MCP Server connects Claude directly with databases, delivering powerful data insights without complicated coding. We help you bridge the gap between natural language and structured database operations.

PostgreSQL MCP Server functionality

The PostgreSQL MCP server turns Claude into your database assistant. It handles essential tasks including:

• Listing all databases in your PostgreSQL server instance

• Showing tables with their complete schema information

• Running read queries to pull the data you need

• Adding or updating records when information changes

• Creating new tables or removing existing ones

• Displaying server configuration details including PostgreSQL version

• Fetching specific server parameter values

The server works with both standard PostgreSQL password authentication and Microsoft Entra authentication methods, though some advanced features only work with the latter.

PostgreSQL MCP Server setup

Getting your PostgreSQL MCP server running takes just a few steps:

1. Open Claude Desktop settings and click the “Developer” tab

2. Select “Edit Config” to modify the configuration file

3. Add this PostgreSQL configuration to the “mcpServers” section:

{
  "mcpServers": {
    "azure-postgresql-mcp": {
      "command": "<path to virtual environment>\azure-postgresql-mcp-venv\Scripts\python",
      "args": ["<path to azure_postgresql_mcp.py file>\azure_postgresql_mcp.py"],
      "env": {
        "PGHOST": "<PostgreSQL instance name>",
        "PGUSER": "<username>",
        "PGPASSWORD": "<password>",
        "PGDATABASE": "<database name>"
      }
    }
  }
}

Restart Claude Desktop after saving these changes. You’ll see a hammer icon at the bottom of your input box when the tools are ready to use.

PostgreSQL MCP Server use cases

This server transforms how you work with databases:

• Database health analysis – check index health, connection usage, and buffer cache

• Query optimization – review execution plans and discover potential indexes

• Schema intelligence – generate SQL that understands your database structure

• Natural language database exploration – understand relationships between customers and invoices

• Performance monitoring – find slow queries and make them faster

• Data visualization – create charts from your query results

The Pro versions add even more capabilities like analyzing replication lag, sequence limits, and vacuum health.

PostgreSQL MCP Server integration with Claude

Once connected, you can talk to your database using everyday language. The integration lets you:

• Describe your database schema through simple questions

• Check recent records with conversational requests

• Visualize how tables connect to each other

• Analyze query performance patterns

• Create visual representations of your data

Claude uses the PostgreSQL MCP server to turn your natural language into SQL queries, run them, and return readable results. The server supports both Standard Input/Output and Server-Sent Events for flexible connection options.

SQLite MCP Server

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SQLite MCP Server brings full database capabilities with minimal setup hassle. We help Claude run SQL queries, analyze data, and generate business insights from lightweight databases without the complexity. Unlike PostgreSQL, this server needs no external database installations – perfect for quick projects and standalone applications.

SQLite MCP Server functionality

The SQLite MCP Server delivers powerful database management through a clean, standardized interface. Key functions include:

• Schema exploration – list available tables and view their detailed structures

• Data management – run read-only queries and make data changes (UPDATE, INSERT, DELETE)

• Statistical analysis – from basic row counting to detailed categorical distributions

• Automatic type detection – with appropriate statistical measures for each data type

• Business intelligence – continuously updated insights memo generation

• Dynamic resource exposure – through memo://insights for easy reference

We build security into every operation with input validation for SQL commands, separation of read-only and modification queries, and protection against SQL injection through parameterized queries.

SQLite MCP Server setup

Setting up SQLite MCP Server needs Python 3.8 or higher and follows these straightforward steps:

1. Install required packages: pip install mcp pandas

2. Download the SQLite MCP server script

3. Add the server to Claude Desktop by editing your configuration file:

"mcpServers": {
  "sqlite": {
    "command": "uv",
    "args": [
      "--directory", "parent_of_servers_repo/servers/src/sqlite",
      "run", "mcp-server-sqlite",
      "--db-path", "~/test.db"
    ]
  }
}

Don’t want to edit config files? Simply set the database location in the DB_PATH environment variable for standalone operation.

SQLite MCP Server use cases

This server shines in several business scenarios:

1. Data analysis for better business decisions

2. Automatic insight generation from datasets

3. Natural language database operations

4. Business intelligence memo creation and maintenance

5. Retail sales analysis and trend identification

SQLite MCP Server integration with Claude

Once connected, Claude works with SQLite databases through everyday language. The server provides tools including:

• read-query: Runs SELECT statements to retrieve data

• write-query: Handles INSERT, UPDATE, DELETE operations

• create-table: Sets up new database tables

• list-tables: Shows all available tables

• describe-table: Provides schema information

• append-insight: Adds business findings to the memo resource

This integration lets Claude analyze business data and automatically create insight memos – turning complex data into meaningful conclusions without requiring database expertise from users.

Google Drive MCP Server

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Google Drive MCP Server connects Claude to cloud-stored documents, moving beyond local file access. This server bridges the gap between AI capabilities and Google’s collaborative workspace tools, giving you secure access to your team’s shared resources.

Google Drive MCP Server functionality

The Google Drive MCP Server helps you manage cloud documents with several key features:

• List, read, and search files across your personal and shared drives

• Automatically convert Google Workspace documents:

  • Google Docs → Markdown

  • Google Sheets → CSV

  • Google Presentations → Plain text

  • Google Drawings → PNG

• Read and write Google Sheets directly

• Search with Google Drive’s powerful query syntax

• Access files through standard URIs: gdrive:///<file_id>

Google Drive MCP Server setup

Setting up Google Drive MCP Server takes a few straightforward steps:

1. Create a Google Cloud project and turn on the Google Drive API

2. Set up your OAuth consent screen (internal settings work fine for testing)

3. Add the OAuth scopes you need:

   • https://www.googleapis.com/auth/drive.readonly for basic file access

   • https://www.googleapis.com/auth/spreadsheets for working with Sheets

For Claude Desktop, add this to your configuration:

{
  "mcpServers": {
    "gdrive": {
      "command": "npx",
      "args": ["-y", "@isaacphi/mcp-gdrive"],
      "env": {
        "CLIENT_ID": "<CLIENT_ID>",
        "CLIENT_SECRET": "<CLIENT_SECRET>",
        "GDRIVE_CREDS_DIR": "/path/to/config/directory"
      }
    }
  }
}

Google Drive MCP Server use cases

We see this server shine when document access and analysis matter most:

• Find and analyze expense reports and financial documents

• Extract key points from company policies

• Process spreadsheet data for business insights

• Build apps that work directly with your Drive files

• Create tools for team document workflows

Google Drive MCP Server integration with Claude

Once connected, Claude works with Google Drive through natural language. No complex commands needed – just ask for what you want in plain English. The setup process is simple:

1. Log in through a browser-based OAuth flow

2. Save your credentials in your config directory

3. Restart Claude Desktop and approve the MCP server

After connecting, Claude can access anything your Google account can see. Your cloud documents become part of the conversation, creating a seamless experience between your cloud storage and AI assistant.

GitHub MCP Server

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GitHub MCP Server connects Claude directly to GitHub’s robust API ecosystem. We’ve designed this server to streamline how you interact with repositories, giving you powerful tools for code management, issue tracking, and project workflows. This official server from GitHub makes development work smoother through AI-assisted automation.

GitHub MCP Server functionality

GitHub MCP Server provides a complete toolkit organized into practical categories:

• Repository operations – manage files, create branches, access commits

• Issue handling – create, read, update, and comment on issues

• User information – access profile data

• Pull request management – create, merge, and review PRs

• Code security features – check for vulnerabilities and scan alerts

We’ve built in customizable toolset selection so you can enable only the specific functions you need through command-line arguments or environment variables. The server also includes dynamic tool discovery—a beta feature that loads toolsets on-demand based on your prompts, cutting down on model confusion that comes from too many tool options.

GitHub MCP Server setup

Setting up GitHub MCP Server needs a few basics:

1. Docker installation (for container-based deployment)

2. GitHub Personal Access Token with the right permissions

For VS Code integration, add this server configuration to your settings:

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "github_token",
        "description": "GitHub Personal Access Token",
        "password": true
      }
    ],
    "servers": {
      "github": {
        "command": "docker",
        "args": [
          "run", "-i", "--rm", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN",
          "ghcr.io/github/github-mcp-server"
        ],
        "env": {
          "GITHUB_PERSONAL_ACCESS_TOKEN": "${input:github_token}"
        }
      }
    }
  }
}

You can also build from source using Go or set up workspace-specific settings with .vscode/mcp.json.

GitHub MCP Server use cases

GitHub MCP Server shines in three main areas:

1. Workflow automation – making repetitive GitHub tasks faster and easier

2. Repository data extraction – getting useful information from your codebases

3. AI-powered tool development – building smarter applications that work with GitHub

These capabilities help your team create more efficient workflows and build better developer tools with AI assistance.

GitHub MCP Server integration with Claude

Once connected, Claude can access GitHub’s extensive API through standardized MCP tools. This lets you interact with repositories using natural language—from looking at code to managing issues and pull requests. You can customize tool descriptions through a configuration file or environment variables to match your workflow preferences. If you’re using GitHub Enterprise, the server works with custom hostnames via the --gh-host flag or GITHUB_HOST environment variable.

GitLab MCP Server

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GitLab MCP Server connects Claude directly with your GitLab projects, issues, and merge requests. This toolkit helps Claude understand your development workflows and collaborate with your team within the GitLab ecosystem.

GitLab MCP Server functionality

The GitLab MCP Server brings several powerful features to your development process:

• Smart branch management – automatically creates branches when needed during file operations

• Clean Git history – preserves your commit timeline without force pushing

• Clear error messages – provides helpful guidance when things go wrong

• Multi-file handling – supports both individual and batch operations

• Pipeline troubleshooting – retrieves console output from failed jobs

• Merge request insights – accesses unresolved comments and feedback

• Change detection – tracks differences between commits and current states

The server opens doors to GitLab’s API for project creation, file management, and team collaboration through issues and merge requests.

GitLab MCP Server setup

You’ll need a GitLab Personal Access Token with the right permissions. Here’s how to get started:

1. Generate your Personal Access Token in GitLab User Settings > Access Tokens

2. Choose your access level: api for full access, read_api for viewing only, or specific read_repository and write_repository scopes

3. Add this to your Claude Desktop configuration:

{
  "mcpServers": {
    "gitlab": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-gitlab"],
      "env": {
        "GITLAB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>",
        "GITLAB_API_URL": "https://gitlab.com/api/v4"
      }
    }
  }
}

Docker users can deploy through container options. If you’re running self-hosted GitLab, just update the GITLAB_API_URL environment variable to your instance.

GitLab MCP Server integration with Claude

Once connected, Claude works with GitLab through natural conversation. You’ll be able to:

• Streamline issue tracking and merge request workflows

• Generate project insights and reports from your data

• Create and update files across multiple projects

• Manage your repositories through simple instructions

This integration helps Claude become part of your development team, understanding your code context and providing support within your workflows. The focused toolset approach keeps things efficient while reducing unnecessary context.

Sentry MCP Server

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Sentry MCP Server brings error tracking and monitoring to Claude, giving AI systems direct access to application errors through standardized protocols. This connector joins AI capabilities with performance insights, helping developers spot and fix issues quickly.

Sentry MCP Server functionality

The Sentry MCP Server delivers robust error monitoring through a clean protocol interface. Key tools include:

• Access to Sentry issues and errors

• Error searching within specific files

• Project and organization queries

• Creation and listing of Sentry DSNs

• Automated error resolution with autofix runs

• Detailed status reporting and information retrieval

The server works as middleware to the Sentry API, letting Claude pull error data and create meaningful performance insights. Though still growing, the server handles both remote and local operation modes.

Sentry MCP Server setup

Setting up the Sentry MCP Server offers several configuration paths:

For MCP-native clients, configuration happens through a mcp_config.json file:

{
  "mcpServers": {
    "Sentry": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp.sentry.dev/sse"]
    }
  }
}

Developers can also run the server locally in STDIO mode:

pipx run mcp-server-sentry --auth-token YOUR_TOKEN

The server works with multiple Claude interfaces – Claude Desktop, Claude.ai, Windsurf, Cursor, and VS Code with GitHub Copilot.

Sentry MCP Server use cases

Though newer to the MCP ecosystem, Sentry’s server powers several practical applications:

• Enhanced bug tracking – scanning error reports and connecting them to project management tools

• Predictive debugging – finding bug patterns before they grow by examining project history

• Natural language insights – querying error data using everyday language

• Cross-platform collaboration – sharing real-time Sentry data between teams

• Automated reporting – building comprehensive error analysis from Sentry data

These tools change how teams handle application errors, moving from fixing problems after they happen to preventing them before they start. Sentry’s toolset improves teamwork between developers, managers, and support staff when tackling application issues.

Brave Search MCP Server

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Brave Search MCP Server connects Claude with the privacy-focused Brave Search engine, giving it real-time web search abilities through MCP protocols. This tool expands Claude’s knowledge beyond its training cutoff, letting it access current information about world events, new products, and recent developments.

Brave Search MCP Server functionality

The server offers two distinct search capabilities:

• Web Search: Runs general queries across websites, news, and articles with custom settings for results count and content freshness. You can request up to 20 results per page and set pagination offset up to 9 for more refined searches.

• Local Search: Finds businesses, restaurants, and services with detailed location information. The system smartly switches to web search when local results aren’t available, making sure you always get useful information.

The server also includes flexible filtering options for controlling result types and safety levels, smart fallbacks to ensure you always get relevant results, and formatted output that’s optimized for Claude to process efficiently.

Brave Search MCP Server setup

Setting up Brave Search MCP Server takes just a few steps:

1. Create a Brave Search API account

2. Pick a plan (the free tier gives you 2,000 monthly queries)

3. Get your API key from the developer dashboard

4. Add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": {
        "BRAVE_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Docker users can use this alternative setup:

{
  "mcpServers": {
    "brave-search": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm", "-e", "BRAVE_API_KEY",
        "mcp/brave-search"
      ],
      "env": {
        "BRAVE_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Brave Search MCP Server integration with Claude

After setup, Claude gets two new tools in its toolkit:

brave_web_search: Takes parameters for your query, how many results you want, and pagination position.

brave_local_search: Accepts local search terms and optional result count settings.

Claude automatically knows when to use these search tools based on your questions. You can ask about breaking news, current events, or local businesses, and Claude will pull fresh information directly from Brave Search. This makes Claude much more helpful for questions about recent developments or local information that wasn’t included in its original training data.

Fetch MCP Server

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Fetch MCP Server works as Claude’s web content specialist. It grabs online information and transforms it into formats Claude can easily digest. This server turns complex HTML pages into clean markdown, letting Claude focus on content rather than code structure.

Fetch MCP Server functionality

Fetch MCP Server brings several powerful web retrieval capabilities to Claude:

• Pulls web content using smart browser automation

• Converts HTML into markdown that’s optimized for AI processing

• Extracts text from images through OCR when needed

• Uses quality scoring to ensure you get the best content

• Handles cookie banners automatically during browsing

• Takes full-page screenshots when necessary

• Adjusts content length based on your needs

The server smartly chooses the best extraction method for each page, delivering clean, structured information from even the most complex websites.

Fetch MCP Server setup

Setting up Fetch MCP Server is straightforward. For Claude Desktop users, just edit your configuration file:

{
  "mcpServers": {
    "fetch": {
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    }
  }
}

Docker users can implement it with:

{
  "mcpServers": {
    "fetch": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "mcp/fetch"]
    }
  }
}

Python fans can install via pip: pip install mcp-server-fetch and run with python -m mcp_server_fetch.

Fetch MCP Server use cases

This server shines in practical applications that matter for businesses:

First, it captures dynamic content from JavaScript-heavy websites that basic scrapers miss completely. It also extracts text from images using OCR, making visually presented data accessible. Finally, it works around anti-scraping measures that would normally block traditional data collection methods.

These capabilities prove invaluable when you need to research current events, gather competitive intelligence, or analyze content across multiple sources. The server helps Claude process real-world web content beyond its training data, making your research faster and more comprehensive.

Puppeteer MCP Server

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Puppeteer MCP Server puts browser automation power in Claude’s hands. We help you create a web-savvy assistant that can navigate sites, capture screenshots, complete forms, and run JavaScript – all within real browser environments.

What Puppeteer MCP Server does

Puppeteer MCP Server gives Claude a complete set of browser tools:

• Navigation tools – Claude visits any website you need with puppeteer_navigate

• Visual capture – Grabs screenshots of entire pages or specific elements

• Form handling – Clicks buttons, fills text fields, and selects from dropdowns

• JavaScript execution – Runs custom code directly in the browser environment

The server also tracks console logs, helping Claude monitor browser activities in real-time. This combination transforms Claude from a conversation partner into a powerful web automation assistant.

Setting up Puppeteer MCP Server

Getting started with Puppeteer MCP Server takes just a few steps:

1. Make sure Node.js is installed on your system

2. Install globally: npm install -g @modelcontextprotocol/server-puppeteer

3. Add this to your Claude Desktop configuration:

{
  "mcpServers": {
    "puppeteer": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-puppeteer"]
    }
  }
}

After saving your configuration, restart Claude Desktop to activate the connection. Don’t want to install? Just run it directly with: npx puppeteer-mcp-server.

How Claude uses Puppeteer

We don’t make you learn technical commands. Just tell Claude what you want in plain English – “Go to this website and extract the pricing information” or “Fill out this form with my contact details.”

Claude translates your natural requests into the right browser operations using Puppeteer’s tools. For security, Claude always asks permission before sensitive actions like navigating to websites or taking screenshots.

This integration opens up practical possibilities:

• Collecting data from websites for your research

• Testing your web applications through simulated user interactions

• Creating screenshots for documentation

• Automating repetitive web tasks that would normally take hours

Slack MCP Server

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The Slack MCP Server turns Claude into your team’s digital collaborator. It creates direct connections with workspace channels, messages, and team members. This smart connector bridges Claude’s AI capabilities with your team’s everyday conversations, creating fluid workflows between AI assistance and human communication.

Slack MCP Server functionality

The Slack MCP Server brings your workspace communication tools into Claude through clean, standardized pathways. It handles several key tasks:

• Posting new messages to any Slack channel

• Responding directly in specific conversation threads

• Adding emoji reactions to messages

• Pulling up lists of public or pre-selected channels

• Retrieving message history from channels

• Accessing all replies within conversation threads

• Gathering user information and profile details

Each function works through dedicated tools like slack_post_message and slack_reply_to_thread, giving you a complete toolkit for workspace interaction. The server manages all the behind-the-scenes work – authentication, formatting, and processing responses between Claude and Slack’s API.

Slack MCP Server setup

Setting up your Slack MCP Server starts with creating a properly configured Slack app:

1. Create a new Slack App through the Slack Apps page

2. Set up Bot Token Scopes including:

   • channels:history – See what’s happening in public channels

   • channels:read – Access basic channel information

   • chat:write – Let the app send messages

   • reactions:write – Add emoji reactions

   • users:read – View user details

After you get your Bot User OAuth Token (starts with xoxb-) and Team ID (starts with T), add this to your Claude Desktop configuration:

{
  "mcpServers": {
    "slack": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-slack"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-bot-token",
        "SLACK_TEAM_ID": "T01234567",
        "SLACK_CHANNEL_IDS": "C01234567, C76543210"
      }
    }
  }
}

If you prefer Docker, that option exists too as an alternative setup method.

Slack MCP Server integration with Claude

Once connected, Claude talks with your Slack workspace using plain language requests. You can simply ask Claude to post messages, look through conversations, or pull up user information without knowing any technical commands.

The system works with both individual and shared authorization models. Individual keeps account connections private to specific users, while shared lets Claude handle requests using one common connection.

This integration creates real workflow improvements – from scheduling meetings across team calendars to analyzing email threads and delivering insights directly to the channels where your team actually works.

Google Maps MCP Server

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Google Maps MCP Server brings location intelligence to Claude. It creates a direct path between Claude and Google’s mapping services through natural language requests. This tool helps AI systems work with geographic data in a straightforward way, making location awareness accessible through standard protocols.

Google Maps MCP Server functionality

The Google Maps MCP Server gives Claude seven core tools that expand what it can do with location data:

• maps_geocode turns street addresses into coordinates, giving you location data and properly formatted addresses

• maps_reverse_geocode does the opposite – it changes coordinates into readable addresses with place IDs and components

• maps_search_places helps find locations using text searches with options to narrow down results

• maps_place_details pulls complete information about specific places, including contact details, ratings, and hours

• maps_distance_matrix figures out travel times between multiple starting points and destinations

• maps_elevation tells you the height at specific coordinates

• maps_directions creates step-by-step navigation instructions between points

Google Maps MCP Server setup

To set up the Google Maps MCP Server, you’ll need a few things first:

1. Node.js (version 14+) installed on your system

2. A valid Google Maps API key

Getting your API key is straightforward:

1. Go to Google Cloud Console

2. Find Google Maps Platform > Credentials

3. Create a new API key and turn on the services you need

Once you have your key, add this to your MCP client configuration:

{
  "mcpServers": {
    "google-maps": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-google-maps"],
      "env": {
        "GOOGLE_MAPS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

If you’re using Windows, you’ll need to modify this slightly to use the cmd command.

Google Maps MCP Server use cases

This server shines in several business applications. Developers can build store locator systems by combining search functions with distance calculations. Delivery businesses can optimize routes and calculate arrival times based on current traffic.

Claude can help create TypeScript or JavaScript code for converting addresses to map coordinates and displaying them. The server also works smoothly with existing systems by transforming data between Google Maps formats and your internal data structures.

20 Must-Know Clauder MCP Servers

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Memory MCP Server

Memory MCP Server gives Claude a persistent memory, keeping important details across multiple conversations through its smart tiered storage system. This intelligent connector helps your AI assistant remember your preferences and history without asking the same questions repeatedly.

How Memory MCP Server Works

Memory MCP Server organizes information through several key components:

• Tiered memory structure that sorts information into short-term, long-term, and archival categories

• Multiple memory types for different kinds of information – conversations, facts, entities, and insights

• Smart search that finds memories based on meaning rather than exact wording

• Automatic memory capture that saves important details without special commands

• Memory transfer that moves short-term information into long-term storage as needed

• Importance ranking that keeps critical information readily available

This system helps Claude remember your preferences, facts, and conversation history naturally – creating a more human-like interaction without the need for explicit “remember this” commands.

Setting Up Memory MCP Server

We offer two straightforward setup methods:

Docker Setup (We recommend this option)

# Clone the repository
git clone https://github.com/WhenMoon-afk/claude-memory-mcp.git
cd claude-memory-mcp
# Start with Docker Compose
docker-compose up -d

Standard Installation

1. Make sure Python 3.8-3.12 is installed

2. Clone the repository: git clone https://github.com/WhenMoon-afk/claude-memory-mcp.git

3. Install dependencies: pip install -r requirements.txt

4. Run setup script: chmod +x setup.sh && ./setup.sh

After installation, add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "memory": {
      "command": "python",
      "args": ["-m", "memory_mcp"],
      "env": {
        "MEMORY_FILE_PATH": "/path/to/your/memory.json"
      }
    }
  }
}

Using Memory with Claude

For the best memory experience, add this to your system prompt:

This Claude instance has been enhanced with persistent memory capabilities. Claude will automatically remember important details about you across conversations and recall them when relevant, without needing explicit commands.

Claude automatically remembers important details from your conversations. Want to check what’s stored? Simply ask natural questions like “What do you remember about me?” or “What do you know about my preferences?”

The memory system works quietly in the background, helping Claude maintain context between different conversations without you needing to manually flag what should be remembered.

Sequential Thinking MCP Server

_{Image Source: Medium}

The Sequential Thinking MCP Server enhances Claude’s reasoning abilities through structured frameworks for complex problems. This tool helps Claude break down challenges into logical steps, creating methodical solutions without losing context.

What It Does

Sequential Thinking MCP Server brings structure to Claude’s thought process through several key capabilities:

• Organizes thinking into clear stages – from problem definition to conclusion

• Tracks thought progression with detailed metadata for later review

• Monitors progress through the reasoning sequence

• Creates concise summaries of the entire thinking process

• Allows for thought revision when new information emerges

Unlike standard approaches, this server helps Claude document each reasoning step, revise earlier thinking when needed, and explore alternative paths when appropriate.

Setting It Up

Adding Sequential Thinking to Claude Desktop requires minimal configuration:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sequential-thinking"]
    }
  }
}

Python developers can implement it with:

from praisonaiagents import Agent, MCP
import os

sequential_agent = Agent(
  instructions="""You are a helpful assistant that can break down complex problems. Use the available tools when relevant for step-by-step analysis.""",
  llm="gpt-4o-mini",
  tools=MCP("npx -y @modelcontextprotocol/server-sequential-thinking")
)

sequential_agent.start("Break down the process of making a cup of tea")

Real-World Applications

This server shines in several practical scenarios:

1. Working through important decisions with clear structure

2. Breaking complex issues into manageable parts Problem Solving

3. Organizing research with defined stages

4. Developing ideas progressively before writing

5. Evaluating projects through systematic analysis

Working With Claude

Once integrated, Claude can use sequential thinking right within your conversation. No need to start a new chat or switch contexts.

The benefits compared to standard reasoning include:

• Maintaining conversation flow without interruptions

• Preserving full context throughout the discussion

• Creating clearly documented reasoning steps

• Allowing revision of earlier thinking

• Working smoothly with other MCP servers

To start using sequential thinking, simply ask Claude to “proceed using the sequential thinking method”. This triggers structured reasoning without breaking your conversation flow.

EverArt MCP Server

_{Image Source: Model Context Protocol}

EverArt MCP Server gives Claude creative visual powers, supporting multiple AI models to produce both vector and raster images. This creative toolkit turns Claude into an artist’s assistant, helping users create visual content from simple text descriptions.

EverArt MCP Server setup

Getting started with EverArt MCP Server begins with an API key from the EverArt website. Once you have your key, you can choose from three setup methods:

For Claude Desktop with NPX:

{
  "mcpServers": {
    "everart": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-everart"],
      "env": {
        "EVERART_API_KEY": "your_key_here"
      }
    }
  }
}

For Docker users:

{
  "mcpServers": {
    "everart": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "EVERART_API_KEY", "mcp/everart"],
      "env": {
        "EVERART_API_KEY": "your_key_here"
      }
    }
  }
}

For developers who prefer building from source:

git clone https://github.com/nickbaumann98/everart-forge-mcp.git
cd everart-forge-mcp
npm install
npm run build

EverArt MCP Server use cases

EverArt shines in creative scenarios where you need to generate images from text. The server supports different models for specific needs:

• Vector Graphics (Recraft-Vector/8000): Creates logos, icons, and scalable graphics with SVG support

• Photorealistic Images (FLUX1.1/5000, FLUX1.1-ultra/9000): Produces lifelike visuals for realistic representations

• Artistic Renderings (SD3.5/6000, Recraft-Real/7000): Generates stylized illustrations and creative concepts

With EverArt, users simply describe what they want in natural language, and Claude handles the technical details. Different models support different formats – SVG is only available with Recraft-Vector, while other models work with PNG, JPEG, and WebP formats.

EverArt includes smart options for managing your generated images, including custom save locations, web project integration, and automatic folder creation. The whole process flows naturally from idea to finished image without complex technical commands.

Stripe MCP Server

Stripe MCP Server links Claude with Stripe’s payment processing system, making financial operations easier through a standard protocol connection. This official server from Stripe makes payment integration simpler for Claude users.

The server works as a bridge between Claude and Stripe’s payment tools, giving users a full payment toolkit. You’ll find tools for:

• Managing customer profiles – creating new accounts and looking up existing ones

• Processing payments – handling transactions from start to finish

• Managing refunds – returning money when needed

• Searching documentation – finding answers in Stripe’s knowledge base

What makes this server particularly useful is its flexible design. Developers can choose which tools to activate through simple command-line options. The server also includes smart tool discovery that only loads what’s needed based on user questions – keeping things running smoothly without overwhelming Claude.

Setting up Stripe MCP Server just needs a valid Stripe API key. You can implement it several ways:

With NPX (the simplest approach):

npx -y @stripe/mcp --tools=all --api-key=sk_test_YOUR_API_KEY

For Cursor users:

{
  "mcpServers": {
    "stripe": {
      "command": "npx",
      "args": ["-y", "@stripe/mcp", "--tools=all"],
      "env": {
        "STRIPE_SECRET_KEY": "sk_test_YOUR_API_KEY"
      }
    }
  }
}

For Claude Desktop:

{
  "mcpServers": {
    "stripe": {
      "command": "npx",
      "args": ["-y", "@stripe/mcp", "--tools=all"],
      "env": {
        "STRIPE_SECRET_KEY": "sk_test_YOUR_API_KEY"
      }
    }
  }
}

Developers who need to test things can use the MCP Inspector to check individual tools and confirm everything works correctly.

After connecting Claude with the Stripe server, the magic happens naturally. Claude recognizes when you’re talking about payments and automatically uses the right Stripe tools. This means you can simply type “Create a new customer with email [email protected] and name John Doe” without knowing any technical commands or Stripe syntax.

This natural language approach works equally well for experienced Stripe developers and newcomers to payment processing – everyone gets to skip the technical hurdles and focus on what they need to accomplish.

Cloudflare MCP Server

Cloudflare has changed the MCP landscape by bringing server connections to the web. While traditional MCP servers lived only on local devices, Cloudflare’s approach makes these connections available anywhere through standard web protocols – no installation needed.

Cloudflare MCP Server functionality

Cloudflare’s web-first approach focuses on making MCP servers accessible and secure through standard internet protocols. Their system includes four main pieces working together:

• workers-oauth-provider – Wraps Worker code with authentication points for simpler security

• McpAgent – Manages remote connections through Cloudflare’s Agent SDK

• mcp-remote – Bridges local MCP clients with web-based servers

• AI Playground – Offers a ready-to-use interface for testing remote connections

This setup works with both public servers (open to everyone) and secure implementations (requiring login). This shift follows the same path we’ve seen with software moving from desktop to web apps, making powerful AI tools available to more people without technical hurdles.

Cloudflare MCP Server setup

Getting started with a Cloudflare MCP Server gives you two main options:

// Basic setup without authentication
{
  "mcpServers": {
    "cloudflare": {
      "command": "npx",
      "args": ["mcp-remote", "https://your-worker.workers.dev/sse"]
    }
  }
}

For servers needing login protection, you’ll implement OAuth flows. Cloudflare makes this easier by supporting connections with existing login systems like Google, GitHub, or your custom solution. Today’s developers can deploy immediately using the “Deploy to Cloudflare” button or through Wrangler command-line tools.

Cloudflare MCP Server integration with Claude

The AI Playground works as a complete remote MCP client, letting you test immediately without extra setup. You simply paste your MCP server URL and handle any login steps if needed. Since Claude Desktop doesn’t fully support remote MCP connections yet, Cloudflare provides the mcp-remote adapter to fill this gap.

These tools let Claude deploy Cloudflare Workers with a single request or work with Cloudflare’s monitoring tools through everyday language. Companies like Stripe, PayPal, Asana, and Atlassian have already used this infrastructure to make their platforms work seamlessly with Claude, creating smooth AI experiences for users everywhere.

Comparison Table

!Image

_{Image Source: Medium}

Our MCP servers guide wouldn’t be complete without a side-by-side comparison. We’ve organized the core details of each server to help you quickly identify which ones match your needs. This table highlights primary functions, key features, setup requirements, and integration methods across the MCP ecosystem.

Each server brings unique capabilities to Claude. Your choice depends on your specific workflow needs, existing tech stack, and the systems you want Claude to interact with. Most servers follow similar integration patterns, making it easy to add new capabilities as your requirements grow.

Conclusion

The Model Context Protocol ecosystem has changed how Claude works with external tools and data sources.

Our guide explored 20 key MCP servers that show important patterns in how they work and what they do.

Filesystem and database servers like PostgreSQL and SQLite create the foundation for data access.

Cloud integration servers such as Google Drive and GitHub extend Claude’s abilities into team environments. Specialized servers like Brave Search and Puppeteer allow Claude to interact with the web beyond its training data.

MCP servers work as modular add-ons that boost Claude’s capabilities without demanding deep technical knowledge from users.

The standardized approach ensures smooth interactions across different tools, creating a more unified experience.

This connection between AI systems and various data sources creates more powerful applications for businesses of all types.

Setting up these servers follows a consistent pattern—getting API credentials, configuring the server with these credentials, and adding it to Claude’s configuration file. While details vary between servers, the basic MCP framework stays consistent, helping developers quickly add new capabilities as they become available.

Security matters tremendously when implementing MCP servers.

Most servers include strong authentication, permission controls, and data validation to prevent unauthorized access or harmful operations.

Users need to follow security best practices when setting up API keys and access tokens.

Want to see how MCP Servers can transform your business operations? Schedule a discovery call with our AI experts at Empathy First Media to find out if your current tech stack and workflows qualify for MCP Server integration.

The future of AI assistants depends on their ability to securely connect with diverse tools and data sources.

MCP servers represent a crucial step toward truly capable AI systems that go beyond conversation into practical applications.

Developers, data engineers, and AI enthusiasts who master these integration points will build more powerful solutions that connect Claude with the digital world, opening new possibilities for automation, analysis, and assistance.

FAQs

Q1. What is the primary function of an MCP server?

An MCP server acts as a bridge between AI models like Claude and external tools or data sources. It enables AI to access real-time information, perform actions in external systems, and communicate using a standardized protocol, making AI more context-aware and capable.

Q2. How do you set up an MCP server for Claude?

Setting up an MCP server typically involves obtaining necessary API credentials, configuring the server with these credentials, and adding the server to Claude’s configuration file. The exact steps may vary depending on the specific MCP server being implemented.

Q3. What are some popular MCP servers available for Claude?

Some popular MCP servers include Filesystem MCP for file management, PostgreSQL MCP for database interactions, Google Drive MCP for cloud document management, GitHub MCP for repository operations, and Slack MCP for workspace communication.

Q4. Are MCP servers secure to use?

MCP servers incorporate various security measures including robust authentication mechanisms, permission controls, and data validation to prevent unauthorized access. However, users must follow security best practices when configuring API keys and access tokens to ensure safe implementation.

Q5. How does Claude interact with MCP servers?

Once an MCP server is integrated, Claude can interact with it through natural language commands. The AI automatically detects available tools and invokes appropriate functions based on user requests, enabling seamless interaction with external systems without requiring technical syntax from users.