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"Importing FastMCP from the mcp.server Python Module" matching MCP servers:

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    A typed FastMCP server that wraps Tavily's web research API, providing tools for search, extract, map, crawl, and research workflows via MCP with prompts and resources.
    8
    MIT
  • A
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    quality
    D
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    A temporally-aware knowledge graph MCP server for AI agents, enabling episodic ingestion, entity management, and semantic search with support for multiple LLM and embedding providers.
    Apache 2.0
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    FastMCP is a comprehensive MCP server allowing secure and standardized data and functionality exposure to LLM applications, offering resources, tools, and prompt management for efficient LLM interactions.
    3
    MIT
  • F
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    A Model Context Protocol server that bridges MCP clients with local LLM services, enabling seamless integration with MCP-compatible applications through standard tools like chat completion, model listing, and health checks.
  • A
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    A Python implementation of the Model Context Protocol that enables applications to provide standardized context for LLMs, allowing developers to build servers that expose data and functionality to LLM applications.
    MIT
  • F
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    quality
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    Exposes a FastMCP server that proxies to an existing LightRAG Server API, enabling querying, document insertion, and management of a LightRAG knowledge base through MCP tools.
  • F
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    quality
    C
    maintenance
    An enterprise-ready MCP server that exposes a RAG tool for retrieving relevant context and metadata from a Qdrant vector database using natural language queries.
    2
  • F
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    Integrates R2R (Retrieval-Augmented Generation) with Claude Desktop, enabling semantic search across knowledge bases and RAG-based question answering with support for vector, graph, web, and document search.
    2
  • A
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    quality
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    Provides tools to fetch and search news from The Verge's RSS feed, allowing users to get today's news, retrieve random articles from the past week, and search for specific keywords in recent Verge content.
    3
    14
    3
    MIT
  • A
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    quality
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    A FastMCP-based MCP server for the R2R API, enabling integration with document management, knowledge graphs, and RAG systems through automatically generated tools and resources.
    MIT
  • A
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    quality
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    A production-grade MCP server and client implementation with comprehensive features including structured logging, health checks, metrics, authentication, and RAG capabilities with PostgreSQL vector search. Supports both stdio and SSE transports with containerization and security features for enterprise deployment.
    MIT
  • A
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    quality
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    maintenance
    Enables retrieval-augmented question answering over a private podcast archive with hybrid search (BM25 + dense embeddings), returning ranked passages with timestamps and citations.
    MIT
  • F
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    quality
    C
    maintenance
    Exposes publisher journalism to LLMs and agent frameworks via search, retrieval, source grounding, and consistent citation, enabling accurate content retrieval with attribution and policy enforcement.
  • F
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    quality
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    A Python port of the official Perplexity MCP server that enables web-grounded Q\&A, deep research, and step-by-step reasoning via Perplexity AI's models. It supports both STDIO and HTTP interfaces for seamless integration with tools like Claude Desktop and Cursor.
  • F
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    quality
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    A Python-based server providing persistent memory management for AI models with SQLite and Markdown dual backend storage. It features full-text search, RAG-enhanced querying, and cross-project knowledge sharing for integration with Claude, Cursor, and Rovo Dev.