"Remote MCP Server Registry/Index" matching MCP servers:

A Streamable HTTP MCP server that provides remote access to ChromaDB for AI assistants like Claude. Enables semantic search and vector database operations from mobile devices and remote locations.

Official Telys MCP server: private, on-device AI memory and retrieval powered by native Mojo kernels. 19 tools: memory CRUD, semantic + BM25 search, single-key filters, compaction/IVF/tuning and self-refreshing repo auto-indexing. Stdio. Introspection needs no credentials; execution requires a one-time free telys login. Source: packages/telys-sdk/telys/mcp.py. Registry: io.github.thyn-ai/telys.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

askDB is an MCP server that retrieves relevant database schema (DDL) from a Pinecone index and provides it to LLMs to write SQL, without connecting to the database itself.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

Enables MCP clients to ingest invoice PDFs into a hybrid-chunked FAISS index, semantically search them, and extract typed invoice data with deterministic arithmetic validation. It also provides listed-company financials and current web search results so agents can research vendors.

Enables natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

Enables any MCP client to index files, directories, and arbitrary text into a local SQLite-backed vector database and perform semantic search with language-aware chunking, filters, and context expansion, all offline without network calls.

RAG MCP server for PDFs, YouTube, GitHub repos, and Discord exports. Index documents and query with citations via LangChain and Chroma.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

A 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.

Enables Claude to search a local hybrid retrieval index of research papers and ingest new PDFs, providing research-paper memory queryable directly through natural language.

Enables MCP-capable coding agents to semantically search, store, and inspect a single local, cross-tool index of session histories and project docs. Agents can retrieve what other tools and prior sessions already discovered.

Enables Claude Desktop to search, add, list, retrieve, reinforce, and delete memories through a remote HTTP memory API, with hierarchical sector classification such as episodic, semantic, and procedural. It also supports connectivity health checks and optional API key authentication for the backing graph and vector store.

Enables AI agents to find local files by meaning rather than exact filename, across Korean and English queries, using a fully local multilingual embedding index on top of voidtools Everything. It also diagnoses and repairs misconfigured Everything settings that cause hangs, with no es.exe or SDK DLL required.

MCP server that indexes uploaded PDF, DOCX, and TXT documents into an isolated per-session in-memory vector index and retrieves the exact matching passages behind each answer. It exposes document indexing and search tools to a Q&A backend so every response is grounded in cited, retrieved evidence.

Local-first knowledge retrieval MCP server that turns private text documents into a source-backed knowledge base, enabling retrieval, comparison, summaries, and review outlines for any local MCP client while keeping source paths and index operations visible.

A Node.js-based MCP server that enables AI agents to generate embeddings, index documents, and perform semantic vector searches using OpenAI and Chroma. It facilitates the creation of retrieval-augmented generation (RAG) pipelines for internal knowledge assistants and document-based workflows.

Enables a single MCP server for interacting with multiple vector databases through pluggable backends, starting with Pinecone. It supports schema-aware index management, upserts, hybrid search, embeddings, TTL conventions, and namespace operations.

Exposes infocepo.com infrastructure (LLM, ChromaDB, S3, Docker registry, service discovery) as MCP tools for AI agents.

A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.

Enables 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.

Enables AI agents to interact with INFINI Easysearch (compatible with Elasticsearch/OpenSearch APIs) through 121 tools covering cluster management, index operations, document manipulation, search queries, snapshots, and monitoring.

Mem0-compatible persistent memory for AI agents - write facts once, recall them semantically in any session. Self-hostable open-source server, or managed cloud with a remote MCP endpoint at https://deepmem.dev/mcp.

This MCP server gives multiple AI tools a shared memory and structured registry while per-client policy controls which facts each can read or write.

Enables MCP clients like Claude, Cursor, and Windsurf to search a local document knowledge base using four-layer retrieval fusion (vector similarity, BM25 keywords, knowledge graph traversal, and metadata filtering) with cross-encoder reranking. Also lets agents index documents, add single documents, list indexed sources, and run health diagnostics, with models kept warm between queries so no GPU, PyTorch, or API keys are needed.

Biblos is a multi-agent MCP server providing shared documented memory and a persistent inter-agent message bus, enabling agents to persist knowledge and hand off work verifiably. It features hybrid searchable Markdown memories, a knowledge graph, agent registry, and identity-verified request queue.

Enables KoboldCpp local models to index and semantically query private documents from multiple file formats via MCP, with privacy-first local processing and zero data leakage.

Enables users to index and retrieve local documents through semantic, BM25, or hybrid search, with tools for chunk reads and page images accessible from MCP clients such as Codex and ChatGPT web.

A high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.

Enables MCP clients to search locally indexed text files, PDFs, and images using natural-language descriptions, and to index folders and inspect index statistics.

A self-hostable remote MCP server that gives multiple AI agents shared, durable, user-owned memory with semantic search, versioned documents, reusable skills, and lessons. It keeps each account isolated while running on the user's own Cloudflare deployment.

Enables Claude to index and retrieve context from codebases using self-hosted Milvus for semantic search, with hardened reliability and security for production use.

A minimal RAG service that exposes a vector index for document retrieval via REST and MCP, allowing querying for relevant document chunks and returning a suggested LLM prompt.

Enables devices and agents to share a self-hosted memory store over a remote Streamable HTTP MCP endpoint, with hybrid retrieval, scoped access tokens, and encrypted vault references for sensitive data.

A local-first semantic search server for documents, supporting PDFs, Office files, and text/markdown, enabling natural language search via the Model Context Protocol (MCP).

Enables indexing and semantic search of software project files via MCP, with automatic file watching for updates.

A remote MCP server enabling semantic memory across multiple AI platforms like Perplexity Comet and Claude Desktop, with vector embeddings for intelligent retrieval.

Gives AI agents a durable, locally hosted temporal memory built from a markdown vault you own, exposing hybrid semantic/lexical/entity search over events, threads, transcripts, entity relationships with validity dates, and patterns with confidence decay. Writes are approval-gated, so agents can draft, commit, and sync new memories while keeping every index rebuildable and nothing leaving your machine.