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Powers an Model Context Protocol (MCP) server with documentation sourced from a local file system.
Provides read-only access to Fathom AI API endpoints for meeting data, transcripts, and summaries through a Model Context Protocol (MCP) server.
Provides philosophical guidance and mentorship using rationalist thinking, Stoic philosophy, and smart contracts.
Empower Claude Code with persistent project memory and a suite of 32 MCP tools for structured knowledge, impact analysis, governance, and task management.
Generates professional software documentation using AI-powered LangGraph workflows and seamless integration with Cursor IDE.
Serves documentation for Expo React Native projects from Markdown files, enabling keyword, fuzzy, and advanced search capabilities.
Indexes Strands Agents documentation into Elasticsearch, serving it via an MCP server for AI platforms and IDEs.
Empowers AI agents with deep workspace intelligence, RAG, and advanced code indexing through a terminal-first IDE.
Exposes real-time Microsoft Flight Simulator 2024 flight data to AI agents via the Model Context Protocol for applications like AI-powered flight instruction.
Generates high-quality educational content tailored to students' knowledge levels and interests using a Model Context Protocol (MCP) server.
Provides an MCP server integration for the Anki flashcard application.
Empower qualitative researchers with AI-driven analysis tools and a community-contributed methodology library.
Explores Retrieval-Augmented Generation (RAG) and Multi-Cloud Processing (MCP) server integration using free and open-source models.
Answers questions about the Peacock VS Code extension by fetching and querying its official documentation.
Establishes a basic Message Control Protocol (MCP) server and client connection.
Powers AI agents with a self-hosted RAG engine, ingesting local web documents and PDFs to provide grounded context via the Model Context Protocol (MCP).
Provides readme and code samples for the Azure Java SDK to AI assistants via the Model Context Protocol.
Enables AI assistants to interact with the Canvas LMS platform.
Provides searchable access to the official Model Context Protocol (MCP) and FastMCP framework documentation, assisting in the development of correct MCP servers.
Provides access to simplified `tldr` command-line documentation as an MCP server.
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