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Enables interaction with FFmpeg for common media operations via a stdio MCP server.
Directory
MCP Server Directory
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
MCP Servers listings
Enables AI assistants to search and access Google Scholar papers through a simple interface.
Analyze SEO data through natural language conversations by connecting Google Search Console with Claude AI.
HA
Hayhooks
CommunityDeploy Haystack pipelines as REST APIs and MCP Tools with ease.
JM
JetBrains Model Context Protocol
CommunityEnables integration between Large Language Models (LLMs) and JetBrains IDEs by providing a server-side implementation for handling Model Context Protocol (MCP) requests and extens…
KC
K8s Connector
CommunityEnables interaction with Kubernetes clusters through Model Control Protocol (MCP) tools.
KO
Kom
CommunitySimplifies Kubernetes operations by providing an SDK-level abstraction of kubectl and client-go, offering easy resource management and MCP server capabilities.
LA
LarkAgentX
CommunityEnables AI agents to perform function calls and message processing directly within Feishu (Lark) without requiring a dedicated bot.
LB
LMStudio Bridge
CommunityEnables Claude to interact with locally running LLM models through LM Studio by providing a Model Control Protocol (MCP) server.
LA
Log Analyzer
CommunityProvides AI assistants access to AWS CloudWatch Logs for analysis, searching, and correlation.
LS
Lsp
CommunityEquips LLMs/AI Agents with language-aware context from codebases by providing Language Server Protocol (LSP) capabilities.
MA
Markmap
CommunityConverts Markdown text into interactive, exportable mind maps.
MC
MCP
CommunitySimplifies building Model Context Protocol (MCP) servers with PHP.
MU
Mcp-Use
CommunityConnect LangChain.js-compatible LLMs with MCP servers for building flexible AI agents with dynamic tool access and multi-server support.
MV
Mise VS Code
CommunityIntegrates the mise tool version manager, environment variable manager, and task runner into Visual Studio Code.
OM
One MCP
CommunityAggregates multiple Model Context Protocol (MCP) servers into a single, unified interface.
OP
OpenAPI Proxy
CommunityExposes REST APIs defined by OpenAPI specifications as Model Context Protocol (MCP) tools, facilitating seamless integration into MCP-based workflows.
OP
OpenStreetMap
CommunityEmpowers LLMs with location-based services and geospatial data from OpenStreetMap.
PV
Package Version
CommunityProvides LLMs with the latest stable package versions for multiple package registries when coding.
PP
Photoshop Python API
CommunityEnables large language models to control Adobe Photoshop via its Python API.
PO
Powerpoint
CommunityAutomates the creation of PowerPoint presentations through a MCP server.
QD
Quick Data
CommunityFacilitates agentic data analysis on JSON and CSV files for AI models like Claude Code.
RA
RagRabbit
CommunityEnables AI-powered search and LLM.txt generation for your website with self-hosting capabilities.
SS
Serper Search and Scrape
CommunityEnables web search and webpage scraping capabilities using the Serper API within MCP-compatible environments.
What Are MCP Servers?
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 →
How MCP Servers Work
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.
Types of MCP Servers
- Code Completion Servers: Enhance AI coding assistants with context from your codebase, documentation, and project structure.
- API Integration Servers: Connect AI to REST APIs, GraphQL endpoints, and web services for real-time data access.
- File Management Servers: Enable AI to read, write, and organize files in your development environment.
- Data Analysis Servers: Connect AI to databases, data warehouses, and analytics tools.
Choosing the Right MCP Server
When selecting an MCP server, consider:
- IDE Compatibility: Ensure it works with Cursor, VS Code, or your preferred editor
- Use Case Match: Choose servers designed for your specific needs
- Maintenance Status: Prefer actively maintained servers with recent updates
- GitHub Activity: Higher stars and recent commits indicate quality
Popular Use Cases
- AI-Powered Code Completion Enhance Cursor and Claude with project-specific context.
- Automated API Testing Connect AI to your APIs for intelligent testing and debugging.
- Database Querying Let AI write and execute SQL queries against your databases.
For detailed setup guides, see our Complete MCP Server Setup Guide →
Frequently Asked Questions About MCP Servers
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
How do I install MCP servers in Cursor?
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.
What's the difference between MCP servers and VS Code extensions?
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.
Are these MCP servers free to use?
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.
Can I build my own MCP server?
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.
What is a Model Context Protocol (MCP) server?
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.
How do MCP servers work with Claude?
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.
What are the best MCP servers to start with?
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.
How do I install and configure MCP servers?
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.
Are MCP servers secure?
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.
What's the difference between MCP resources, tools, and prompts?
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.
Which AI clients support MCP besides Claude Desktop?
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.
How often is this MCP servers directory updated?
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.
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