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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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    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
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    Enables full-text search of macOS iMessages including link preview metadata. Works as an MCP server for Claude Desktop to search your messages locally.
    1
    MIT
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    Enables AI systems to perform full-text and semantic search operations over structured/unstructured data in Azure Cognitive Search, with capabilities for document indexing and management through natural language.
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    ISC
  • A
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    MCP server that aggregates job listings from Remotive and Arbeitnow, with local SQLite caching, application tracking, and saved searches.
    75
    MIT
  • A
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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
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    MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.
    MIT
  • A
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    A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.
    GPL 3.0
  • F
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    Retrieves comprehensive patient information including personal details, insurance plans, and employee data through the get_patient tool. Supports Docker Compose deployment and integration with Watson Orchestrate for healthcare data access.
  • F
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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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    A Model Context Protocol server that searches transcript segments in a Turso database using vector similarity, allowing users to find relevant content by asking questions without generating new embeddings.
    4
  • F
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    A private MCP server that converts natural-language questions into embeddings and performs semantic retrieval over document chunks stored in BigQuery, returning structured passages with source and page metadata. It serves as the read-only retrieval layer for a document-grounded chatbot.
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    Downloads your entire Search Console dataset into a local SQLite database, then gives your LLM a pre-built SQL query library for every standard SEO analysis type, with context available for your LLM to perform any SQL query to answer your questions and analyse for you.
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    Apache 2.0
  • A
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    Connect AI assistants to Manticore Search. Execute SQL queries, list tables, get schemas, and fetch documentation. Perfect for building RAG applications and search-powered AI agents.
    5
    4
    Apache 2.0
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    Provides access to Naver Search APIs, allowing AI agents to search across multiple categories (blogs, news, books, images, shopping items, etc.) with structured responses optimized for LLM consumption.
    13
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    Apache 2.0
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    Enables searching for any text within a specified Algolia index through an MCP-compatible interface. It allows users to integrate Algolia search capabilities into their environment using an application ID and API key.
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    MIT