Browse Model Context Protocol (MCP) servers and integrations.
Model Context Protocol (MCP) servers are standardized interfaces that allow large language models and AI agents to securely interact with external systems, tools, and data stores. Instead of relying on bespoke integrations, an MCP server exposes defined tools, resources, and prompts over a unified protocol. This architecture enables AI coding assistants, desktop agents, and autonomous workflows to query databases, manipulate local files, execute terminal commands, and call external APIs with fine-grained control.
This directory catalogs 1186 active MCP servers structured across 20 functional domains. Developers can browse servers organized by target environment and capability, including Databases & Data Stores for querying relational and vector backends, Developer Tools & Code Intelligence for IDE enhancements, and DevOps, CI/CD & Version Control for deployment automation. Additional domains include Cloud & Infrastructure, Security & Compliance, Browser & Web Automation, AI Memory & Context, and Files, Documents & PDFs. Each category groups servers designed to grant models access to specific operational layers without requiring custom middleware.
Selecting the right MCP server depends on your client environment, transport protocol, and execution runtime. First, confirm compatibility with your AI client, such as Claude Desktop, Cursor, Windsurf, or custom agent runtimes built on the MCP SDK. Second, inspect the server transport type; most run locally over standard input/output (stdio), while others operate remotely via Server-Sent Events (SSE) or WebSockets. Finally, evaluate the required permission scopes and authentication mechanisms. Production workflows benefit from servers that enforce read-only modes or explicit confirmation prompts prior to executing destructive actions on your infrastructure.
| MCP server | What it connects to | Type | Repository |
|---|---|---|---|
| Qwen-Agent | Qwen-Agent is an open-source framework and agent platform that connects Qwen large language models to tools, planning workflows, memory, and | Open Source | https://github.com/QwenLM/Qwen-Agent |
| Qlik Cloud | Qlik Cloud is an MCP server that connects large language model clients to the Qlik Cloud API to query analytics | Unknown | https://github.com/jwaxman19/qlik-mcp |
| RewindDB | RewindDB is an MCP server that interfaces with the local Rewind.ai SQLite database to expose recorded audio transcripts and optical | Unknown | https://github.com/pedramamini/RewindMCP |
| Rhombus MCP Server | Rhombus MCP Server is an MCP server that integrates the Rhombus physical security and surveillance API with LLM clients like | Unknown | https://github.com/RhombusSystems/rhombus-node-mcp |
| Routine | Routine is an MCP server that connects AI assistants like Claude Desktop to the Routine desktop productivity application. Designed for | Unknown | https://github.com/routineco/mcp-server |
| WebRTC MCP Chat Server | A remote WebRTC chat server with secure temporary rooms and MCP support for background agents. | Unknown | https://github.com/brysgo/webrtc-mcp-chat |
| QuantConnect | QuantConnect is an MCP server that bridges large language models like Claude and OpenAI models to the QuantConnect cloud algorithmic | Unknown | https://github.com/QuantConnect/mcp-server |
| Rowan | Rowan is an MCP server that integrates LLM-based assistants with the Rowan computational chemistry platform. Designed for computational chemists, medicinal | Unknown | https://github.com/k-yenko/rowan-mcp |
| PDF Tools | PDF Tools is an MCP server that provides document manipulation utilities directly to large language models through the Model Context | Unknown | https://github.com/hanweg/mcp-pdf-tools |
| PHP MCP Server for Laravel | PHP MCP Server for Laravel is an MCP server that exposes Laravel application functionality as standardized Model Context Protocol tools, | Open Source | https://github.com/php-mcp/laravel |
An MCP server is an application that implements the Model Context Protocol to expose data, tools, and prompts to AI assistants. It standardizes how models read external context and trigger actions in external systems.
Clients supporting MCP include Claude Desktop, Cursor, Windsurf, Continue, and various open-source autonomous agent frameworks that implement the Model Context Protocol client specifications.
The majority of MCP servers are open-source and free to run locally. However, some servers interface with third-party commercial APIs, cloud providers, or proprietary platforms that require paid subscriptions or API keys.
Developers can submit a server by providing its repository link, documentation, supported transport protocols (stdio or SSE), license type, and category classification through the FastPedia submission form.
Listings are ranked using objective criteria, including repository maintenance activity, implementation completeness, documentation quality, community usage signals, and protocol compliance.
MCP servers execute locally with the permissions of the host environment. Users should inspect server source code, verify required file system and network privileges, and configure client-side approval prompts before granting execution rights.