Skip to main content
Glama
mecoskun

Sourcebook

by mecoskun
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to Sourcebook

No user-submitted related servers found.

    Related Servers

    • mcp-rag-server

      kwanLeeFrmVi
      A
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).
      22 npm
      36
      MIT

    • ragi

      SusuTawar
      A
      license
      A
      quality
      D
      maintenance
      Local-first RAG indexing and semantic search MCP server. Enables document retrieval and context-aware queries using local embedding models.
      3
      13 npm
      MIT

    • mcp-docpilot-server

      shishirreddyyk
      F
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that exposes document retrieval as tools (semantic search and source listing) for any LLM, using a vector index built from DocPilot's ingestion pipeline.
      -

    • mcp-ragdocs

      hannesrudolph
      A
      license
      Not graded
      quality
      D
      maintenance
      An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context
      19 npm
      265
      MIT

    • MCP PDF to PGVector

      sanskritiparmendranaval
      F
      license
      Not graded
      quality
      C
      maintenance
      MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.
      -
    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

    A3.7/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct operation: indexing, listing, deleting, and searching documents. There is no meaningful overlap in purpose, so an agent should have no trouble selecting the right tool.

    Naming Consistency4/5

    All names follow a clear verb_document(s) snake_case pattern, with verbs positioned first. The only minor inconsistency is the singular/plural noun form depending on whether the operation targets one document or a collection.

    Tool Count5/5

    Four tools is a well-scoped surface for a source-document workspace: add, list, search, and delete. Each tool serves a distinct core need without unnecessary bloat.

    Completeness4/5

    Core document lifecycle coverage exists: index, list, search, and delete. The main gaps are the lack of an explicit update/refresh operation and a full-document retrieval tool, though these can be worked around by deleting and re-indexing or by using search results.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources