Work History
Logs AI tool activities with detailed tracking of metrics, models, and timestamps to daily markdown files.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Logs AI tool activities with detailed tracking of metrics, models, and timestamps to daily markdown files.
Teaches large language models (LLMs) to understand and replicate user workflows recorded with PSR.exe.
Integrates WorkFlowy's outline and task management features with LLM applications through an MCP server.
Synchronizes work activities across Harvest, Linear, and Slack, featuring automated daily standups and AI-powered time tracking.
Exposes WordPress tools and actions to Large Language Models (LLMs) and agents via a Model Context Protocol (MCP) server.
Compose AI assistants with this library.
Wraps Xcode CLI tools, summarizing verbose outputs to reduce LLM token usage, thereby accelerating development workflows and boosting reliability.
Manages project-specific and knowledge graph-based memory for LLMs and agents.
Enables calling iFlytek workflows through Model Context Protocol (MCP) tools.
Enables manipulation of Excel files through native COM automation via a Model Context Protocol (MCP) server utilizing xlwings.
Enables querying live XML Documents data from applications like Claude Desktop using CData JDBC Drivers.
Enables AI agents to interact with the XMTP decentralized messaging network using the Model Context Protocol.
Provides secure access to the Xplainable AI platform, enabling the management, deployment, and explanation of machine learning models.
Enables AI models to interact with and retrieve data from the XRP Ledger.
Transforms coding agents into voice-enabled companions by providing real-time audio notifications and interactions.
Integrates AI assistants with the Yandex Tracker task management system via the Model Context Protocol.
Enables AI agents to control and interact with the Unity game engine through the Model Context Protocol (MCP).
Provides a Model Context Protocol (MCP) server for YeePay Open Platform (YOP), enabling AI assistants to access platform information, manage keys, and download certificates.
Integrates YouTrack's extensive capabilities with various applications via a Model Context Protocol (MCP) server, streamlining issue tracking, project management, and team collabo…
Transforms YouTube into a queryable knowledge source, powering AI workflows and detailed content analysis.
Enables AI models to control YouTube Music playback through Google Chrome.
Enables AI assistants to download and analyze YouTube video subtitles.
Fetches or generates YouTube video transcripts using AI, prioritizing official transcripts and falling back to local Whisper transcription.
Enables AI assistants to interact with Zammad tickets, users, and organizations through a standardized Model Context Protocol interface.
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.