Skip to main content
Glama
61,048 servers. Last updated

Matching MCP tools:

Matching MCP Connectors:

"RAG (Retrieval-Augmented Generation) system that can store papers and web pages" matching MCP servers:

  • A
    license
    B
    quality
    D
    maintenance
    Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.
    Last updated
    1
    Apache 2.0
  • F
    license
    -
    quality
    B
    maintenance
    MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.
    Last updated
  • A
    license
    -
    quality
    D
    maintenance
    Enables LLMs to interact with vehicle CAN bus and OBD-II data through a simulated ECU environment. Provides tools for reading frames, decoding messages via DBC files, monitoring signals, and querying automotive diagnostics without requiring physical hardware.
    Last updated
    9
    MIT
  • F
    license
    -
    quality
    D
    maintenance
    Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.
    Last updated
  • A
    license
    -
    quality
    D
    maintenance
    An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.
    Last updated
    10
    MIT
  • -
    license
    -
    quality
    -
    maintenance
    Single MCP server that manages multiple personal collections (todos, bookmarks, etc.) with only six generic tools, driven by a YAML registry for validation.
    Last updated
  • F
    license
    -
    quality
    D
    maintenance
    Exposes two MCP tools (discover and execute) that enable agents to query an OpenAPI schema via natural language and execute matched API operations.
    Last updated
  • A
    license
    A
    quality
    C
    maintenance
    An MCP server that scans code repositories for app store rejection risks by mapping API usage to required declarations and policy deadlines, enabling agents to catch issues before submission.
    Last updated
    5
    MIT
  • F
    license
    A
    quality
    D
    maintenance
    Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.
    Last updated
    1
    2
  • F
    license
    C
    quality
    D
    maintenance
    A server that implements Retrieval-Augmented Generation using GroundX and OpenAI, enabling semantic search and document retrieval with Modern Context Processing for enhanced context handling.
    Last updated
    3
  • A
    license
    -
    quality
    D
    maintenance
    A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.
    Last updated
    MIT
  • A
    license
    -
    quality
    D
    maintenance
    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
    Last updated
    4
    Apache 2.0
  • A
    license
    -
    quality
    D
    maintenance
    A Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.
    Last updated
    1
    MIT