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Open-source all-in-one AI framework for semantic search, LLM orchestration, and language-model workflows, built around an embeddings database that unions sparse and dense vector indexes, graph networks, and relational databases, with pipelines, workflows, agents, and web and MCP APIs.

Connect Claude to Jina AI's Reader, Search, Embeddings, and Reranker APIs — read URLs as clean markdown, run web and academic searches, extract PDFs, and rerank results — with the official Jina AI remote MCP server.

Open-source AI data infrastructure for storing documents, embeddings, metadata, and retrieval indexes across local, self-hosted, and managed Chroma Cloud deployments.

Connect Claude to Qdrant for read-only semantic search or opt-in semantic memory storage through the official MCP server.

Apache-2.0 Python framework from Hugging Face for dense embeddings, sparse embeddings, semantic search, reranking, multimodal retrieval, and embedding-model training.

Connect Claude to a Weaviate vector database — run hybrid search, inspect collection config, list tenants, and upsert objects — using Weaviate's built-in Model Context Protocol server.

Official Pinecone Developer MCP server that connects Claude and other MCP clients to Pinecone projects and documentation for index management, record upserts, semantic search, cascading multi-index search, reranking, and documentation lookup over integrated-inference indexes.

Official Chroma MCP server for connecting Claude to Chroma collections, documents, semantic search, full-text search, metadata filtering, persistent storage, self-hosted Chroma, and Chroma Cloud.

Document intelligence MCP server for extracting text, metadata, OCR output, structured data, embeddings, chunks, cache state, and supported-format information from PDFs, Office files, images, code, and many other formats.

Official MariaDB MCP server for schema inspection, read-only SQL, optional database creation, and vector-store search against MariaDB databases.

MCP server from Zilliz for connecting Claude to Milvus vector database collections, text search, vector search, hybrid search, inserts, deletes, indexes, collection loading, database switching, and collection metadata.

Open-source AI memory platform that gives agents persistent long-term memory by ingesting data in any format and building a self-hosted knowledge graph, combining vector embeddings, graph reasoning, and ontology generation for meaning-based and relationship-based retrieval.

MCP server for semantic codebase intelligence, combining AST structure, embeddings, clustering, feature hubs, restore points, and memory graph tools.