Mnē-MCP
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Alternatives to Mnē-MCP
No user-submitted related servers found.
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- FlicenseNot gradedqualityBmaintenanceEnables AI-powered chat and file operations on Obsidian vaults with local indexing, hybrid search, and MCP access.-
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to search, read, create, update, and delete notes in a local Obsidian vault through hybrid semantic and lexical retrieval, with all embedding and vector storage running locally.MIT
- FlicenseAqualityDmaintenanceEnables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.4-
- AlicenseNot gradedqualityAmaintenanceProvides a RAG system for your Obsidian Vault using DuckDB and vector search, enabling semantic search and note retrieval through AI agents.2MIT
- AlicenseNot gradedqualityAmaintenanceEnables 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.15MIT
- AlicenseNot gradedqualityCmaintenanceEnables semantic search over an Obsidian vault using natural language, retrieving relevant notes and extracted conclusions.MIT
TDQS
Scored across 7 tools
Each tool has a distinct role: indexing, LLM-based querying, raw vector search, deletion, listing, stats, and config. Query and search are clearly separated by whether the LLM is involved.
All tool names are lowercase, single-word commands that follow a consistent imperative/noun style. The set is uniform and predictable despite not using a verb_noun pattern.
Seven tools is well-scoped for a focused memory/RAG server. Each tool covers a necessary operation without redundancy or bloat.
The toolset covers the full indexed-document lifecycle: add via index, retrieve via search/query, remove via delete, inspect via list and stats, and configure via config. No critical missing operation is apparent.