"A local knowledge base" matching MCP servers:

Enables agents to search, read, list, and amend a git-backed markdown knowledge base, automatically committing and publishing changes.

A personal knowledge base MCP server that allows AI assistants to manage notes, tasks, and ideas through tools, resources, and prompts.

Gives AI agents a shared persistent memory by ingesting Obsidian vaults, code, transcripts, web clips, and session or bug-fix captures, then serving token-optimized context briefings, keyword and semantic search, and cross-source synthesis. Enables multiple agents to read and write the same growing knowledge base so each session builds on the last.

A lightweight personal knowledge base MCP server that lets clients store, search, organize, and summarize research notes from a local JSON file.

Enables AI agents to share a persistent, self-improving memory by ingesting sources like Obsidian vaults, code, transcripts, and session captures, then serving them back through search, classification, synthesis, and token-optimized context briefings. It lets multiple agents read and write the same knowledge base, so each session builds on the last without copy-pasting context.

Gives AI agents a shared persistent memory by ingesting notes, code, transcripts, bookmarks, and session captures into a SQLite FTS5 knowledge base they can search, read, classify, promote, and synthesize over MCP. This lets multiple agents retrieve tiered, token-optimized context and compound what they learn across sessions instead of starting from zero.

Provides coding agents with a shared, Markdown-based engineering knowledge base to search, capture, create, and update internal conventions, API details, infrastructure configs, and development setup via lightweight MCP tools.

Enables AI tutors to maintain durable, local-first learning state by modeling goals as prerequisite-aware knowledge trees, reusable concepts, and evidence-gated mastery.

Enables Claude to save, retrieve, update, search, and organize personal ideas and reusable analytical frameworks in a private SQLite-backed knowledge base. Supports local desktop use or always-on access across a user's own devices over a private network.

A local MCP server for managing Markdown notes, enabling create, list, read, search, summarize, and delete operations through natural language.

Enables Claude Code to interact with Obsidian vaults by providing tools for multi-term searching, reading notes, and exploring tag-based relationships. It allows users to query, analyze, and manage their personal knowledge base directly through natural language.

Enables AI assistants to manage a personal markdown-based knowledge base with natural language interactions. Supports creating, searching, updating, and organizing notes across categories like people, recipes, meetings, and procedures.

A bridge server that allows LLM tools to interact with an Obsidian vault through a local REST API, enabling file operations, note management, and metadata access through natural language.

A local, zero-cost MCP server that fact-checks your Markdown/Obsidian notes using a local LLM (via Ollama) and free sources like Wikipedia and DuckDuckGo, with no cloud API or API keys.

Enables building and managing knowledge workspaces with tools for ingesting content from text, clipboard, or URLs and searching organized knowledge bases. Supports multiple configurable workspaces with separate inbox and knowledge directories for structured information management.

Enables AI agents to read, search, and write to a public wiki knowledge base via MCP.

Enables AI agents to share a persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from sources like Obsidian vaults, code, and transcripts through MCP and REST APIs. Provides token-optimized, tiered retrieval with full-text and semantic search so every agent session builds on accumulated context.

Enables AI agents to capture, classify, synthesize, and retrieve persistent shared knowledge from sources such as Obsidian, code, transcripts, bookmarks, and sessions. It provides token-efficient search, context briefings, and tiered memory through MCP and REST APIs.

Enables AI agents to share a persistent, self-learning memory by ingesting and classifying knowledge from Obsidian, code, transcripts, bookmarks, and terminal sessions, then retrieving token-optimized context through MCP and REST APIs.

Local markdown notes for any MCP client: ranked + semantic search, tags, todos, a wiki-link knowledge graph, daily notes, templates, and slash-command workflows. Pure-JS, local, no API keys.