Skip to main content
Glama
masseater

Gemini RAG MCP Server

by masseater
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Related Servers

Alternatives to Gemini RAG MCP Server

No user-submitted related servers found.

    Related Servers

    • notebooklm-api

      mcpware
      A
      license
      A
      quality
      D
      maintenance
      Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.
      7
      1 npm
      2
      MIT

    • kbdb

      diko316
      A
      license
      B
      quality
      A
      maintenance
      Enables file-based knowledge management with ranked keyword and semantic hybrid search, allowing AI agents to learn from documents and recall relevant knowledge as a persistent memory tool.
      30
      56 npm
      AGPL 3.0

    • Chalee MCP RAG

      PrettyKing
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables RAG (Retrieval-Augmented Generation) capabilities with document processing, vector storage, and intelligent Q\&A using OpenAI embeddings and semantic search.
      -

    • MCP RAG Server

      0xrdan
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI assistants to search and retrieve information from your knowledge base using RAG (Retrieval-Augmented Generation) with hybrid search, document indexing, and ChromaDB vector storage.
      15 npm
      MIT

    • knowledge_mgmt

      mmaun
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables uploading, organizing, and semantically searching documents with support for various file types and embedding providers.
      59 npm
      MIT

    • ParseFlow MCP Server

      Libres-coder
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI assistants to parse and search documents including PDF, Word, Excel, PowerPoint, and images via OCR, with support for semantic search and batch processing.
      2
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.5/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: querying for answers, uploading text content, and uploading files. There is no overlap in functionality, and an agent can easily tell them apart based on their specific roles in the RAG workflow.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (query, upload_content, upload_file) with clear, descriptive terms. The naming is uniform and predictable, making it easy for agents to understand and use the tools.

    Tool Count4/5

    With 3 tools, the server is well-scoped for a RAG system, covering core operations: querying, uploading text, and uploading files. It is slightly lean but reasonable, as it handles the essential workflow without unnecessary complexity.

    Completeness4/5

    The tool set covers the main RAG operations: ingestion (uploading content/files) and retrieval (querying). Minor gaps might include tools for managing or deleting uploaded content, but the core functionality is complete for basic RAG use cases.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources