Skip to main content
Glama
thebrownproject

RagLit MCP Server

by thebrownproject
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Related Servers

Alternatives to RagLit MCP Server

No user-submitted related servers found.

    Related Servers

    • rag-mcp

      NextLevelManagementAdvisors
      A
      license
      A
      quality
      B
      maintenance
      Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.
      4
      AGPL 3.0

    • fathom-mcp

      veer-mehta
      A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to ingest documentation from websites or local files and perform semantic search over the indexed content using pgvector-backed embeddings.
      5
      1
      MIT

    • Istedlal MCP Server

      AnshuML
      F
      license
      B
      quality
      D
      maintenance
      Provides AI agents with access to file metadata, vector search, and workflow metrics. It enables operations such as file metadata retrieval and semantic search over file embeddings using pgvector.
      3
      -

    • RAG-MCP Knowledge Base Server

      Luxter77
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables semantic search across text documents using vector embeddings stored in PostgreSQL. Provides multiple search modalities including semantic similarity, question/answer, and style-based search through a retrieval-augmented generation system.
      3
      Apache 2.0

    • MCP Knowledge Base Server

      maxsmosarski
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables semantic search and document management with support for text, PDF, and image uploads using your own Supabase database and OpenAI API keys. Supports multi-tenant deployment on Cloudflare Workers or local hosting.
      -
    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

    C2.1/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool targets a distinct step in the RAG pipeline: chunking documents, searching chunks, and filtering by metadata. The purposes are clearly separable based on names alone, with no overlapping actions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: chunk_document, search_chunks, filter_metadata. This creates a predictable and readable naming convention.

    Tool Count4/5

    Three tools is on the lower end of the well-scoped range (3-15), but it covers the core RAG operations without being sparse. The count is reasonable for a focused server, though slightly minimal.

    Completeness4/5

    The tool set covers the essential lifecycle for a simple RAG server: ingest (chunk), retrieve (search), and refine (filter). Minor gaps exist, such as lack of explicit document management or chunk retrieval, but the core workflow is functional.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources