Explore our complete collection of MCP servers to connect AI to your favorite tools.
Integrates with SearXNG to provide privacy-focused meta search capabilities.
Enables LLM agents to interact with Industry Foundation Classes (IFC) files.
Enables developers to build intelligent, document-based Retrieval-Augmented Generation (RAG) applications.
Enables seamless communication between AI Agents and Hologres databases for metadata retrieval and SQL operations.
Delivers hourly weather forecasts using the AccuWeather API within an MCP environment.
Simplifies management of Model Context Protocol (MCP) servers and their integration across different clients.
Enables text-to-speech capabilities using the Rime API, playing audio through the system's native audio player.
Provision instant, private, sandboxed environments for common services like databases and message queues, perfect for local development and AI agent integration.
Dynamically creates new tools for use with MCP clients based on natural language descriptions.
Integrates Notion into AI workflows through a Model Context Protocol (MCP) server, allowing AI agents to interact with Notion pages and databases.
Enables AI agents to interact with the DataWorks Open API for seamless cloud resource operations.
Provides access to real-time Indian Railway data, including train searches, seat availability, and live status updates.
Implements a minimalistic MCP server using a bash script for basic mathematical operations.
Provides an asynchronous Python SDK for TickTick, combining official and unofficial APIs, and includes an MCP server for AI assistant integration.
Integrates Gyazo images into AI workflows via the Model Context Protocol.
Manages records and files within a PocketBase instance, providing tools for data manipulation and migration management.
Empowers security teams with AI-driven threat intelligence analysis, identifying and attributing threats across multiple sources.
Enables natural language interaction with the TON blockchain for analytics, forensics, and real-time data access.
Enhances code editing experiences by providing language support features.
Automate kit workflows with a lightweight, high-performance, and flexible engine for cloud or self-hosted environments.
Optimizes and manages context for AI models, improving prompt efficiency, response quality, and reducing costs.
Integrates Model Context Protocol (MCP) server capabilities into ElysiaJS applications with HTTP transport.
Provides Claude with the current time and timezone information via the Model Context Protocol (MCP).
Connects AI models with FalkorDB graph databases via the Model Context Protocol.
Enables Large Language Models (LLMs) to interact directly with Couchbase clusters for data access and manipulation.
Coordinates agents by hosting finite state machines as dynamic resources, enabling real-time updates based on state changes.
Injects auto-approve functionality into the Claude Desktop application.
Generates images from text prompts using Google's Gemini Flash models through the MCP protocol.
Enables interaction with LLMs using mcp.run tools via a Python library.
Enables AI assistants to break down user requests into manageable tasks with subtasks, dependencies, and notes.
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