Meilisearch
Enables interaction with Meilisearch through Large Language Model (LLM) interfaces via a Model Context Protocol (MCP) server.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables interaction with Meilisearch through Large Language Model (LLM) interfaces via a Model Context Protocol (MCP) server.
Provides a basic implementation of an MCP server.
Connects Large Language Models to open data sources using the Model Context Protocol.
Integrate popular agent frameworks with PayPal APIs through function calling.
Provides persistent, searchable local memory for AI assistants, LLMs, and Copilot within VS Code.
Enables remote control of Android devices via ADB commands within an MCP environment.
Enables reading and writing to a Pinecone index via the Model Context Protocol, facilitating retrieval-augmented generation (RAG).
Provides access to Polygon.io financial market data via a Model Context Protocol (MCP) server, enabling LLMs to retrieve real-time and historical market information.
Integrates with the Postman API to enable comprehensive management of Postman collections, environments, and APIs.
Enables developers to implement Model Context Protocol (MCP) server features easily within Quarkus applications.
Generates charts using the QuickChart.io service through Model Context Protocol (MCP).
Integrates web search capabilities into AI assistant frameworks using the Exa API for real-time, markdown-formatted results.
Enables large language models to securely read, manage, and operate Salesforce resources.
Connects large language models to Salesforce data through SOQL queries and SOSL searches.
Search for accurate academic articles from various scholarly sources.
Provides search and crawl functionality using Search1API through a Model Context Protocol (MCP) server.
Connects AI models to SEC EDGAR filings through an open-source MCP server, enabling financial research and insights.
Enables Claude to interact with ServiceNow instances by providing a Model Completion Protocol server implementation.
Executes whitelisted shell commands remotely with standard input support.
Enables LLMs to search and access scientific papers from arXiv.
Exposes macOS Siri Shortcuts to Large Language Models (LLMs) via the Model Context Protocol (MCP).
Explore AWS EC2 Spot instance types, savings, prices, and interruption frequencies for optimal cloud resource selection.
Connects to the Strava API to provide tools for accessing fitness data through Large Language Models.
Enables communication between Roblox Studio and Claude Desktop via a plugin, allowing LLMs to interact with and modify the Roblox environment.
MCP (Model Context Protocol) servers are tools that connect AI assistants like Claude, Cursor, and other AI coding tools to external data sources, APIs, and services. They enable AI models to access real-time information, execute code, interact with databases, and perform actions beyond their base capabilities. Check out our curated collection of the best MCP servers for Cursor →
MCP servers act as intermediaries between AI assistants and external systems. When you ask Claude or Cursor to perform a task requiring external data, the MCP server handles the request, fetches the data, and returns it in a format the AI can understand and use.
When selecting an MCP server, consider:
For detailed setup guides, see our Complete MCP Server Setup Guide →
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
To install MCP servers in Cursor: 1) Open Cursor settings (Cmd+,), 2) Navigate to MCP Servers section, 3) Click 'Add Server', 4) Enter server configuration (name and command), 5) Restart Cursor. Check out our curated collection of the best MCP servers for Cursor with detailed setup guides.
MCP servers are protocol-level integrations that work across multiple AI assistants (Claude, Cursor, etc.), while VS Code extensions are editor-specific. MCP servers provide context to AI models, whereas extensions add IDE functionality. MCP is more portable and AI-focused.
Most MCP servers listed are open-source and free. Some enterprise connectors (like Salesforce or Jira) may require paid API access to the underlying service, but the MCP server code itself is usually free.
Yes! The Model Context Protocol is open standard. You can build servers in Python or TypeScript/Node.js to expose your own internal APIs or databases to Claude and Cursor.
An MCP server is a lightweight program that exposes specific capabilities (data access, tool execution, prompts) to AI assistants through a standardized protocol. MCP servers allow Claude and other AI models to securely interact with external systems like databases, APIs, file systems, and web services while maintaining security boundaries.
MCP servers connect to Claude Desktop or other MCP-compatible clients through a standardized JSON-RPC protocol. When you configure an MCP server in Claude Desktop, Claude can access its resources (data/content), use its tools (functions to execute), and leverage its prompts (templated interactions). The protocol ensures secure, controlled access to external capabilities.
Essential MCP servers for beginners include: Filesystem (local file access), SQLite/PostgreSQL (database queries), GitHub (repository access), Brave Search (web search), and Memory (persistent context). These cover common use cases and have excellent documentation. Start with 2-3 servers and expand based on your needs.
Most MCP servers install via npm (npx) or Python (uvx/pip). Configure them in Claude Desktop's config file (claude_desktop_config.json) by specifying the command, arguments, and any required environment variables like API keys. Our directory links to each server's documentation with specific installation instructions.
MCP servers run locally on your machine with explicit permissions you configure. They can only access resources you authorize, and Claude cannot bypass these boundaries. However, always review server code, use official/verified servers when possible, limit permissions to what's necessary, and be cautious with servers that request broad access.
Resources are data sources Claude can read (files, database results, API responses). Tools are functions Claude can execute (run queries, send messages, create files). Prompts are pre-defined templates for common interactions. Most MCP servers expose one or more of these capability types.
MCP is supported by Claude Desktop (official), Cursor IDE, Continue (VS Code extension), and various community implementations. The protocol is open, so support is expanding to more AI development tools. Check our compatibility filters to find servers tested with your preferred client.
Our MCP servers directory is updated weekly with new servers, documentation improvements, and compatibility updates. We monitor GitHub releases, community contributions, and Anthropic announcements to ensure our listings reflect the latest MCP ecosystem developments.