open-zk-kb

open-zk-kb

Gives AI assistants persistent, shared memory using the Zettelkasten method, so they retain corrections, preferences, and decisions across sessions and across tools via local, hybrid search.

Category
Visit Server

README

open-zk-kb

CI npm version npm downloads License: MIT

You open a new session and your agent has no idea who you are. Again. You re-explain your stack, your conventions, that one edge case you've corrected five times.

open-zk-kb gives your agent a memory — so corrections stick, context compounds, and every session starts smarter than the last.

<p align="center"> <a href="docs/pi.md"> <img src="assets/pi-demo.gif" alt="Store, apply, inspect, and remove an automatic preference in Pi" width="760"> </a> <br> <sub>The full loop in Pi: store a preference, carry it into a fresh session, inspect the vault, and remove it when it stops being useful.</sub> </p>

Quick start

Requires Bun — install with curl -fsSL https://bun.sh/install | bash

bunx open-zk-kb@latest

The installer configures your selected clients, installs agent instructions, and creates a local vault. Supported clients: OpenCode, Claude Code, Cursor, Windsurf, Zed, Pi, and OMP.

See the Setup Guide for manual installation and troubleshooting.

Why open-zk-kb?

Your agent starts from zero every session. No memory, no learning curve. You correct the same mistakes, re-explain the same conventions, re-teach the same context. Switch tools and it's even worse — your Cursor agent doesn't know what your Claude agent learned.

open-zk-kb fixes that.

  • Correct it once, it sticks — your agent stores corrections, preferences, and decisions. Next session, it already knows.
  • Works across every tool — one knowledge base shared by Claude Code, Cursor, Windsurf, OpenCode, Zed, Pi, and OMP
  • Finds what's relevant — hybrid search matches meaning, not just keywords, so only useful context surfaces
  • Runs locally — no API keys, no cloud, works offline. Your data stays on your machine.
  • Human-readable — plain Markdown files you can browse, edit, and version control
  • Open source — MIT licensed

Pi: native knowledge tools

Install the Pi package, then restart Pi:

pi install npm:open-zk-kb

The extension exposes all ten knowledge-* tools directly in Pi. Results use Pi-native compact rendering: search, store, context, and health have focused summaries and expandable detail, while the other tools show concise status output. The MCP server and local SQLite/embedding work still run with Bun >= 1.0; Pi itself runs under its supported Node.js runtime. Installing Bun is therefore required even when using the Pi package.

Pi also loads active project preferences automatically when a session starts and injects them into model context without requiring a model-initiated search. The visible knowledge-context entry reports what happened without fabricating a tool call.

See the Pi experience guide for the complete preference workflow and renderer examples. For installer-managed instructions, verification, and troubleshooting, see Pi installation.

Configuration

Zero configuration required. Local embeddings work out of the box with no API key.

See the Configuration Guide for embeddings, vault path, lifecycle tuning, and server settings.

Under the hood

Built on the Zettelkasten method — atomic, linked notes with structured kinds. Each note captures one concept (a decision, a preference, a gotcha) and links to related notes, building an interconnected knowledge graph.

Search combines SQLite FTS5 full-text indexing with local vector embeddings (MiniLM-L6-v2) for semantic matching. Markdown files are the source of truth; the database is a rebuildable index.

Telemetry

When enabled (telemetry.enabled: true and telemetry.share: true), open-zk-kb sends one anonymous event for each completed session to PostHog (EU Cloud) on a later startup. It includes a canonical client, bounded model IDs, vault size, and counts for all ten tools—not note content, queries, paths, names, or email addresses. Runtime defaults are disabled; the interactive installer enables sharing only after affirmative consent, while unattended and direct package installs remain disabled unless configured separately. Set DO_NOT_TRACK=1 to unconditionally block sharing (local SQLite counters are unaffected), or keep both flags false. See Telemetry for the full event schema and details.

Documentation

License

MIT License

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured