"A localized 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 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.

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.

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.

Enables AI agents to share persistent memory by capturing, classifying, synthesizing, and retrieving knowledge through token-optimized, three-tier retrieval with hybrid keyword and semantic search. Supports bidirectional Obsidian sync, session and bug-fix capture, and a self-learning loop that compounds context across sessions.

Enables AI agents and clients to capture, classify, synthesize, and retrieve persistent knowledge from multiple sources through MCP and REST APIs, with tiered memory and token-optimized context.

An MCP server that utilizes Trello as a knowledge base for storing, searching, and retrieving code snippets and notes. It enables full CRUD operations and organized categorization of information using Trello boards and labels.

Enables AI agents to share persistent memory by ingesting, classifying, synthesizing, and retrieving knowledge through MCP and REST APIs, with token-optimized, tier-aware search and Obsidian sync.

Enables AI agents to share persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from Obsidian vaults, code, documents, transcripts, bookmarks, and sessions through MCP and REST interfaces with token-optimized search.

Enables sandbox-less frontends such as mobile apps to reach the WeRead official gateway over Streamable HTTP by supplying only a URL and an access token, with no local process required. Exposes 14 read-only tools covering search, shelf, notebooks, reading progress and statistics, highlights, public reviews, and recommendations, plus a token-protected dashboard for shelf, notes, and shared-reading annotations.

Enables AI agents to capture, classify, synthesize, and retrieve persistent knowledge from sources like Obsidian, code, web clippings, transcripts, bookmarks, terminal sessions, and fixes, using FTS5 and semantic search through MCP and REST interfaces.

Enables AI agents to search, read, create, and maintain a local-first knowledge base using hybrid retrieval and Markdown note management through the Model Context Protocol.

A Cloudflare Workers-based MCP server for Notion knowledge base management, enabling intelligent search, automatic recording of code snippets, and statistics analysis through natural language.

Enables AI agents to share persistent memory by capturing, classifying, synthesizing, and retrieving knowledge from sources like Obsidian, code, and transcripts via MCP and REST APIs. Provides token-optimized search, three-tier memory, and self-learning capture of sessions and fixes so multiple agents can build on prior context.

A zero-dependency MCP server that provides a persistent personal knowledge base for Claude using local JSON file storage. It enables users to manage notes through tools for adding, searching, and indexing content built entirely with Node.js built-ins.

Enables access to a notes knowledge base via MCP, providing tools for keyword search, note creation, and retrieval, along with browseable note resources.

Enables AI agents to capture, classify, promote, synthesize, and retrieve persistent knowledge from sources such as Obsidian vaults, code repos, YouTube transcripts, bookmarks, terminal sessions, and bug fixes. Exposes tiered cold/warm/hot memory with token-optimized search, context briefings, and cross-source synthesis so multiple agents share one compounding brain across sessions.

Enables AI agents to capture, classify, synthesize, and retrieve persistent knowledge through MCP and REST APIs, with SQLite FTS5 search, tiered memory, and token-optimized context so multiple agents share and compound context across sessions.