Knowledge Graph
Provides an MCP server enabling AI assistants to directly access and query a German family business knowledge graph database.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides an MCP server enabling AI assistants to directly access and query a German family business knowledge graph database.
Transforms text and web content into structured knowledge graphs using local AI models, with persistent storage and real-time visualization.
Integrates with Kommo CRM to manage leads, contacts, companies, and provides advanced analytics and reporting functionalities.
Translates natural language prompts into Kusto Query Language (KQL) queries and executes them against a Kusto database.
Connects Large Language Models to Kuzu databases, enabling schema inspection and query execution through the Model Context Protocol.
Implements LangGraph to interact with a PostgreSQL database via an MCP server.
Interfaces with LibSQL databases, providing schema information and enabling table queries.
Facilitates interaction with Alibaba Cloud's Lindorm multi-model NoSQL database through a suite of tools for data retrieval and management.
Enables interaction with PostHog analytics to create annotations and manage projects through Claude Desktop or Smithery.
Provides seamless access to academic literature databases, enabling researchers to accelerate their literature review process with LLMs and MCP clients.
Manages PostgreSQL database interactions using an AI agent powered by LlamaIndex and a local Ollama LLM.
Integrates Model Context Protocol (MCP) servers with SQLite databases, enabling natural language interactions via LlamaIndex and Ollama-powered clients.
Provides AI assistants with direct, read-only access to Local by Flywheel WordPress databases, enabling informed SQL queries and schema understanding.
Provides comprehensive logging, aggregation, and real-time monitoring capabilities for all MCP services with integrated analytics.
Provides long-term memory storage for LLMs, enabling them to retain context across multiple sessions by leveraging semantic search and embeddings.
Provides a Model Context Protocol server for MariaDB database operations, enabling interaction with Claude Code and other MCP clients.
Enables AI assistants to interact with and query MariaDB databases via the Model Context Protocol (MCP).
Enables AI models to query and retrieve comprehensive materials science data from the Materials Project database via a Model Context Protocol server.
Enables interaction with Matomo Analytics through modern JavaScript/TypeScript libraries.
Provides a Model Context Protocol (MCP) server for interacting with databases like PostgreSQL and DuckDB, and accessing Google Cloud Storage Parquet files.
Analyzes log files by creating an SQLite database and interacting with it using the Model Context Protocol (MCP) SQLite server.
Integrates MongoDB with the Model Context Protocol (MCP) to enable AI assistants to interact with databases.
Extends the mem0 cloud service to provide project memory storage, semantic search, and structured data handling for project management.
Manages memories programmatically with local storage, semantic search, and OpenAI embeddings.
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.