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"Exploring RAG through defined workspaces" matching MCP servers:

  • A
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    quality
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    A privacy-preserving local RAG system integrated with MCP, enabling natural language queries over ingested documents and a SQLite database through vector search and local database tools.
    MIT
  • A
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    quality
    B
    maintenance
    Connects to a PostgreSQL database (pgvector) to perform semantic retrieval via the search_documents tool, returning raw document snippets for LLM synthesis.
    1
    GPL 3.0
  • A
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    quality
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    Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.
    MIT
  • F
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    quality
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    Enables semantic search and retrieval of code files using embeddings stored in PostgreSQL. Supports intelligent codebase exploration through natural language queries, file listing, and content retrieval.
    16
  • F
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    quality
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    Enables RAG (Retrieval-Augmented Generation) with tools for vector search, document access, and OpenAI integration, plus MySQL storage and file system operations via MCP.
  • A
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    quality
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    A powerful AI service platform that provides complete MCP tool calling capabilities and RAG knowledge base functionality, enabling users to connect to multiple MCP servers and perform intelligent document search.
    Apache 2.0
  • A
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    quality
    C
    maintenance
    MCP server platform enabling agents to self-register and access geo MCP tools (read-only geo_entities) plus hello ping services via a public MCP endpoint.
    MIT
  • F
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    quality
    B
    maintenance
    Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.
    5
  • F
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    Enables AI copilots to understand and query Salesforce org configurations through intelligent metadata chunking and semantic search. Provides access to Apex classes, custom objects, flows, layouts, and other metadata with hybrid vector and keyword search capabilities.
  • A
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    quality
    A
    maintenance
    Enables AI applications to integrate with Tableau through tools, resources, and prompts for querying data, exploring content, and retrieving visualizations from Tableau workbooks and datasources.
    11,978
    321
    Apache 2.0
  • A
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    quality
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    maintenance
    Enables LLMs to interact with Dremio data platforms for querying, analyzing data patterns, and exploring metadata through natural language, with support for both local and production Kubernetes deployments.
    52
    Apache 2.0
  • A
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    quality
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    maintenance
    Enables secure read-only access to PostgreSQL databases through SELECT queries only, with tools for exploring schemas, listing tables, and executing common queries while preventing any data modification operations.
    505
    MIT