mcp server

grounded-knowledge-engine

Local-first engine that grounds an AI agent's answers in your own Markdown and captures what it learns back into the KB — Node · TypeScript · MCP.

dimosgit/grounded-knowledge-enginecommunitylistedunreviewed

Use tool

Set up

Runs on your computer. Pick your agent and operating system.

This project does not publish an install method we can turn into a config. Follow the README instead.

README

synced Oct 21, 2026

Grounded Knowledge Engine

Local-first, provider-neutral project memory for AI coding agents.

Grounded Knowledge Engine (GKE) gives Claude Code, Codex, Gemini CLI, and other MCP clients durable context across sessions. It retrieves evidence from local files, answers with file-and-line citations, captures useful learning when you request it, and resumes structured project state without turning a database or hosted service into the source of truth.

Your Markdown remains canonical. Retrieval indexes are derived and disposable, and every workspace stays on your machine.

https://github.com/user-attachments/assets/d00c977b-9538-4835-94d5-26350136eb34

What GKE does

Grounded answers with file-and-line citations and strict abstention.
Durable capture back into Markdown; risky changes enter a review queue.
Project resume as a cited briefing: focus, decisions, blockers, next steps.
Document ingestion for PDF, DOCX, XLSX, PPTX, HTML, and more.
One local MCP server for Claude Code, Codex, Gemini CLI, and Copilot.

It is not a hosted chat memory, team wiki, or document-management platform.

Quick start

GKE requires Node 22.5 or newer; Node 24 is recommended.

Install the current release:

npm install --global https://github.com/dimosgit/grounded-knowledge-engine/releases/download/v0.2.1/grounded-knowledge-engine-0.2.1.tgz

Create the verified demo workspace and configure supported clients:

gke demo
cd gke-demo
gke setup

Restart Claude Code or Codex from gke-demo, then ask:

Use GKE to resume the router-rollout project.

Continue with the five-minute golden path to retrieve cited evidence, retain one learning, and retrieve it again from a fresh session.

The core loop

Index or ingest local evidence, answer with citations, capture what was learned back into Markdown, and resume the project in a later session.

MCP surface

The default core profile exposes four tools: kb.search, kb.get_record, kb.answer_and_capture, and kb.resume_project. Retention is update-first: new findings are appended to the record that owns them. The full profile adds advanced retrieval, decisions, and explicit write tools. See the MCP server reference.

Your own workspace and documents

gke setup --workspace client-alpha --workspace-root "/path/to/client-alpha"
npm run ingest -- ./inbox --dry-run

Each named workspace runs as its own process, with writes disabled by default. See workspace configuration and the ingestion guide.

Operator Cockpit

An optional local view for project attention, capture and decision review, and a context graph. Try the public demo or read the Cockpit guide.

Learn more

Golden path · Boundaries · Data model · Copilot · Agent workflows · Contributing

License

MIT. The demo knowledge base includes paraphrased notes from the MIT-licensed MCP documentation; see demo sources.