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maintenanceMCP server for semantic search over PDF documents using RAG, pgvector, and OpenAI embeddings. Includes a web app for document upload and management.
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"How to scrape web content" matching MCP servers:
- AlicenseAqualityAmaintenanceMulti-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.10MIT
Tribalofficial
FlicenseAqualityAmaintenanceSemantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.109- AlicenseAqualityBmaintenanceEnables Claude to scrape, crawl, extract data, and sync to vector databases using scrapedatshi's RAG pipeline, with support for multiple embedding and vector DB providers.12MIT
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- AlicenseAqualityDmaintenanceA Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.355Apache 2.0
- FlicenseAqualityDmaintenanceIntegrates R2R (Retrieval-Augmented Generation) with Claude Desktop, enabling semantic search across knowledge bases and RAG-based question answering with support for vector, graph, web, and document search.2
- AlicenseAqualityDmaintenanceIndexes codebases using semantic embeddings for natural language search, enabling developers to find code with queries like 'how does authentication work'.81MIT
- AlicenseAqualityDmaintenanceProvides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.63MIT
- AlicenseAqualityDmaintenanceAn experimental MCP server that makes YouTube playlist transcripts available for AI assistants, enabling search and conversation about video content.13Apache 2.0
- FlicenseAquality-maintenanceEnables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.893
mcp-server-qdrantofficial
AlicenseBqualityCmaintenanceThis repository is an example of how to create a MCP server for Qdrant, a vector search engine.21,499Apache 2.0- FlicenseBqualityDmaintenanceEnables semantic search and contextual conversations with your Calibre ebook library using vector-based RAG technology. Supports project-based organization, multi-format book processing, and OCR capabilities for enhanced content extraction and retrieval.72
- FlicenseBqualityDmaintenanceA Model Context Protocol server that enables semantic vector search over Obsidian notes, allowing AI assistants to intelligently search and retrieve relevant note content.12
- FlicenseBqualityDmaintenanceEnhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.124
- AlicenseBqualityDmaintenanceEnables fetching relevant content and embeddings from Supavec via the Model Context Protocol, allowing AI assistants like Claude to access vector search capabilities.294MIT
- AlicenseBqualityDmaintenanceMCP server providing context usage estimation, conversation compaction, and durable semantic memory via local embeddings and SQLite.1793MIT
- AlicenseBquality-maintenanceEnables AI assistants to interact with Meilisearch through a standardized interface, supporting index and document management, search capabilities, settings configuration, task monitoring, and experimental vector search.68
- AlicenseBqualityDmaintenanceEnables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.1Apache 2.0
- FlicenseCqualityDmaintenanceEnables storing and retrieving information using vector embeddings with semantic search capabilities. Integrates with the AI Embeddings API to automatically generate embeddings for content and perform similarity-based searches through natural language queries.2