MCP RAG
Related Servers
Alternatives to MCP RAG
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityBmaintenanceMCP server that enables semantic search over PDF documents using RAG with ChromaDB and OpenAI embeddings.-
- AlicenseNot gradedqualityCmaintenanceAn 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. Uses Ollama or OpenAI to generate embeddings. Docker files included10 npm30MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).15 npm37MIT
- AlicenseAqualityDmaintenanceLocal-first RAG indexing and semantic search MCP server. Enables document retrieval and context-aware queries using local embedding models.35 npmMIT
- AlicenseNot gradedqualityCmaintenanceSelf-hosted RAG MCP server that enables semantic and hybrid search over document corpora using local FAISS embeddings, with tools for indexing, retrieving chunks or full documents, uploading files, and managing multiple corpora via MCP.MIT
- FlicenseNot gradedqualityBmaintenanceMCP server for semantic search over PDF documents using RAG, pgvector, and OpenAI embeddings. Includes a web app for document upload and management.-
TDQS
Scored across 11 tools
Most tools have distinct purposes, but there is some overlap between 'add_file' and 'add_memory' as both involve adding data, though to different systems (RAG vs. memory). Similarly, 'search_files' and 'search_memory' are distinct but conceptually similar operations. The descriptions help clarify the boundaries, but an agent might occasionally confuse these pairs.
All tool names follow a consistent verb_noun pattern with snake_case, such as 'add_file', 'clear_data', 'get_stats', and 'search_memory'. This uniformity makes the set predictable and easy to understand, with no deviations in style or convention.
With 11 tools, the count is well-scoped for a RAG and memory management system. It covers core operations like adding, removing, listing, and searching for both files and memory, along with utility functions like clearing data and testing connections, without being excessive or sparse.
The tool set provides comprehensive coverage for RAG and memory operations, including CRUD-like actions for files and memory entries, search capabilities, and system management. A minor gap is the lack of tools for updating existing files or memory entries, which might require workarounds, but core workflows are well-supported.