Search across your Obsidian vaults using hybrid, semantic, or keyword modes to retrieve context, notes, and past decisions.
Apache 2.0
260,522 tools. Last updated 2026-07-05 07:02
"A server for searching and retrieving information using keyword, semantic, or hybrid search methods" matching MCP tools:
- Search a knowledge base using semantic, keyword, or hybrid methods to find relevant information from vectorized content.MIT
- Search knowledge bases with hybrid semantic and keyword queries to find relevant information chunks with relevance scores.
- Hybrid search combining keyword and semantic matching to find Obsidian vault notes, even when query terms differ from note content. Filter by metadata for precise results.MIT
- Search your personal memory layers by combining vector similarity with keyword matching to retrieve relevant episodic, semantic, and procedural memories.AGPL 3.0
- Find relevant information from your PDF knowledge base using semantic search. Retrieve cited excerpts from indexed documents by combining multiple databases.AGPL 3.0
Matching MCP Servers
- Alicense-qualityAmaintenanceMCP server that indexes Obsidian notes and enables hybrid search (full-text, fuzzy, semantic) for AI assistants to find and read notes.Last updated1,01681MIT
- Alicense-qualityDmaintenanceEnables searching for a keyword within a text file using Model Context Protocol tools via standard input/output.Last updated2451MIT
Matching MCP Connectors
Search PubMed and summarize biomedical literature — designed for AI health agents.
Search the web, images, videos, news, and local businesses with robust filters, freshness controls…
- Search indexed datasets by keyword or meaning to find specific documents without reprocessing files. Supports structured, semantic, and hybrid modes with optional filters.MIT
- Retrieve stored information from long-term memory using semantic meaning, keywords, or both to provide context about topics when users ask questions.MIT
- Search digital assets using vector or keyword queries. Use natural language filters to locate specific assets.ISC
- Get related keyword suggestions with search volume and competition data from a seed keyword. Expand keyword research with long-tail variations and new cluster candidates.MIT
- Search documents using semantic understanding to find relevant content based on meaning rather than keywords. Understands natural language queries and returns ranked passages with source information.MIT
- Search prior decisions and past sessions using hybrid vector and keyword search. Retrieve ranked results from your capsule library with titles, summaries, tags, and scores.MIT
- Find relevant documentation chunks from a repository by searching indexed docs with semantic or keyword search. Returns results with file paths for direct reading.MIT
- Find skills that match your task description using semantic search, with fallback to keyword matching from GitHub.MIT
- Search across project knowledge (instructions, runbooks, session docs) using hybrid keyword and semantic search. Returns relevant chunks with source file, section, and line numbers.Business Source 1.1
- Find relevant information from curated skills and documents using natural language queries. Semantic search leverages vector embeddings for more accurate results than keyword search.MIT
- Search code skeletons using natural language queries to find methods, classes, and namespaces ranked by semantic similarity. Filter results by project, file path, or code unit type.MIT
- Recall relevant memories from an AI agent's storage using hybrid search (vector + FTS5 + keyword).MIT
- Search for LPM packages using natural language or structured filters. Find packages by category, ecosystem, distribution, license, and more.ISC
- Search daily memory files on the OpenClaw server for a keyword. Customize the search range up to 90 days (default: last 14 days).Apache 2.0