"An MCP server for indexing S3 content into a RAG vector database" matching MCP servers:

Enables AI assistants to securely search and retrieve information from a user's encrypted Joplin notebook via vector memory and MCP.

A local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.

Enables semantic and keyword search over Obsidian-style Markdown knowledge bases by registering any folder as a vault, with support for incremental indexing, raw source reads, and cache-backed embeddings over MCP stdio.

Answers questions about a folder of markdown notes using hybrid retrieval that fuses FTS5 keyword search and vector search, then reranks results with a cross-encoder.

MCP server for summarizing content from Baidu Netdisk, local files, Bilibili, X, and web articles, producing Obsidian notes with bidirectional links and Feishu digests.

MCP server that integrates with LM Studio to provide a search_notes tool, allowing the chat model to retrieve and answer from a local Obsidian vault.

Enables semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.

A live MCP server that connects AI assistants to a running Obsidian instance, enabling full app automation including reading notes, clicking UI elements, managing plugins, and executing JavaScript.

MCP server for hybrid retrieval over markdown vaults, combining sqlite-vec embeddings and FTS5 keywords with reciprocal rank fusion, plus optional cross-encoder reranking.

Enables semantic search over an Obsidian vault using natural language, retrieving relevant notes and extracted conclusions.

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

Enables semantic search and content retrieval from local Obsidian vaults through the Model Context Protocol. It allows AI assistants to query notes by meaning, filter by tags, and access full note content for enhanced knowledge integration.

Enables natural-language semantic search over a fully local knowledge base, keeping embeddings, storage, and retrieval on the machine.

Enables semantic search and retrieval over an Obsidian vault using local or API-based embeddings, allowing AI assistants to find notes by meaning, get related content, and pull context during conversations.

Enables semantic search over personal markdown notes by indexing them into a vector database and exposing search, reindex, and status tools via MCP.

Provides semantic search over Obsidian markdown notes using BAAI/bge-m3 embeddings and ChromaDB, accessible via the Model Context Protocol.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Enables AI agents to search, create, and manage Notion pages and databases through the Model Context Protocol. It features file-based operations and response extraction to optimize token usage and context efficiency.

Enables MCP clients to search and read recorded meeting data, including transcripts, notes, action items, and participants, from Walkie's local database.