MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.
Enables forwarding Douyin or Bilibili video shares to Kimi for AI analysis and automatically writing the resulting Chinese notes into an Obsidian vault.
Enables automatic collection and AI analysis of Slack messages to create organized Notion pages, supporting custom analysis directions like meeting minutes, issue extraction, and topic classification.
Surfaces forgotten notes from markdown vaults using wikilink graph structure and file mtime to identify dormant notes, then generates cross-domain bridge queries for serendipitous rediscovery.
Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.
Enables users to manage a personal to-do list backed by SQLite, adding single or multiple tasks, listing incomplete tasks, renaming or updating task status, and marking tasks complete. All state persists in a local database created automatically on first run.
Enables AI assistants to run the real Obsidian Tasks query language against a Markdown vault via MCP, supporting filters, relative dates, dependencies, grouping, sorting, and query explanations without requiring Obsidian to be running.
Self-hosted MCP server that provides embedding-powered semantic search with graph context over Obsidian vaults, supporting multiple vaults, local embeddings, and a web dashboard.
A zero-config personal knowledge management MCP server that enables Claude Desktop to automatically classify, search, and organize local Markdown notes using hybrid search and Graph RAG.
Converts rough notes into a citation-grounded report, verifying each claim against source notes and handing off to SuperDocs with a faithfulness circuit breaker.
Enables fast local hybrid search over a folder of markdown files via MCP, combining BM25 and vector similarity with explicit relevance verdicts and no LLM or network calls at query time.