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Builds AI agents that interact with the Starknet blockchain using multiple AI providers.
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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
SO
SonarQube
CommunityEnables seamless integration with SonarQube Server or Cloud and allows for code snippet analysis within the agent context.
SH
Streamable Http
CommunityProvides example implementations of Model Context Protocol (MCP) Streamable HTTP client and server in Python and TypeScript.
SW
Swagger
CommunityServes Swagger/OpenAPI specifications through the Model Context Protocol.
TI
TikTok
CommunityIntegrates TikTok access into applications via TikNeuron.
TK
Tool Kit
CommunityProvides an agentic abstraction layer for building high precision vertical AI agents in Python.
TR
Txtai.rs
CommunityProvides Rust bindings for the txtai API, enabling semantic search, LLM orchestration, and language model workflows within Rust applications.
VE
Vectorize
CommunityImplements a Model Context Protocol (MCP) server that integrates with Vectorize for advanced vector retrieval and text extraction.
WI
Wikipedia
CommunityRetrieves information from Wikipedia to provide context to Large Language Models (LLMs).
WX
Wxflows
CommunityProvides examples and tutorials for building AI applications using the watsonx.ai Flows Engine.
XP
Xcode Project
CommunityManipulates Xcode project files programmatically using the Model Context Protocol.
ZE
Zettelkasten
CommunityImplements the Zettelkasten knowledge management methodology, enabling creation, linking, exploration, and synthesis of atomic notes.
Generate and validate Terraform IaC via MCP with Terraform Registry access.
AC
Agent Care
CommunityFacilitates integration of healthcare tools and prompts with FHIR data on EMRs like Cerner and Epic.
AA
Agentic AI Demos
CommunityProvides example implementations for building agentic AI solutions with AWS, utilizing the Model Context Protocol.
AI
All-In-One
CommunityProvides an all-in-one Model Context Protocol (MCP) server with AI search, RAG, and integrations for services like GitLab, Jira, and Confluence.
AS
Apache Spark History
CommunityEnables AI agents to connect with Apache Spark History Servers for intelligent job analysis and performance monitoring.
AC
Azure CLI
AzureEnables interaction with Azure resources through the Model Context Protocol (MCP).
CA
Chat Application
CommunityEnables intelligent chat applications through the Model Context Protocol, supporting both web and desktop environments.
CH
ChatExcel
CommunityProvides an intelligent server for Excel file analysis, data processing, code execution, and interactive chart generation using the Model Context Protocol.
CC
Claude-C2
CommunityEnables command and control communication with Claude using a Python server and PowerShell client.
CO
Codebase
CommunityIndexes codebases locally as an MCP service, enabling semantic search and integration with AI development tools like Claude Code and Gemini CLI.
CO
Coincap
CommunityRetrieves cryptocurrency data from the Coincap API without requiring API keys or registration.
CR
Cryo
CommunityProvides API access to Cryo's blockchain data extraction capabilities via the MCP protocol.
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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