Kage

Name: Kage
Author: kage-core

by kage-coreversion 2.3.0i★ –iRuns on your computer

Registry namecom.kage-core/kage

Install

Overview

Description from the maker (original English)

Verified memory for coding agents: claims cited against code, stale withheld, savings receipts.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "kage": {
      "command": "npx",
      "args": [
        "-y",
        "@kage-core/kage-graph-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add kage -- npx -y @kage-core/kage-graph-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "kage": {
      "command": "npx",
      "args": [
        "-y",
        "@kage-core/kage-graph-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "kage": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@kage-core/kage-graph-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain kage-core.com (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7264 servers in this category
Published to the registry more recently than 16% of the other 7264 servers in this category
Basic checks equal to or better than 100% of the other 7264 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Kage safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.3.0) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Kage manages your memory and agents

State an intent. Kage's orchestrator briefs a coding agent from your repo's own memory, runs it in an isolated git worktree — a single run or a multi-wave goal — and re-runs the checks itself rather than trusting the agent's report:

┌ VERIFIED 3/3 — checks run by Kage, not the agent · build-a-stale-memory-triage-surface-do-n-260818-ec2c

│ "the stale-memory triage surface is built and wired into the review flow" │ ✓ tests ran npm test --prefix mcp → exit 0 evidence/tests.log │ ✓ diff-size inspected at most 800 changed lines evidence/diff-size.log │ ✓ citations inspected every formally cited path exists (directly, or as a unique suffix) in the worktree evidence/citations.log │ · touched 4 file(s), 212 line(s) └────────────────────────────────────────────────────────────────

A real receipt from this repo's own run history. Every row is a command Kage ran or a fact it inspected — never a claim the agent made about itself. kage merge only lands the code once the claim holds, and ratifies what the agent learned, so the next brief, yours or a teammate's, starts smarter.

That memory is the decisions behind your codebase, the runbook for a tricky deploy, the root cause of a gnarly bug — captured as your agents work and checked against the actual code, so what gets reused stays true. It's kept as plain Markdown files in your repo, conformant to the Google Open Knowledge Format (OKF) so there's no lock-in, and shared with your whole team through git. No account, no database, no API key.

npx -y @kage-core/kage-graph-mcp install

Website · Docs · Live viewer · npm · Book a demo

Works with Claude Code · Codex · Cursor · Windsurf · Gemini CLI · Cline · Goose · Roo Code · Kilo Code · OpenCode · Aider · Claude Desktop · Copilot · OpenClaw · Hermes · any MCP client

🌐 English · 简体中文 · 日本語 · 한국어 · Español · Português (Brasil) · Français · Deutsch · हिन्दी

Install

One command, inside your repo, then restart your agent. That's the whole setup.

npx -y @kage-core/kage-graph-mcp install

It creates .agent_memory/, builds the code graph, writes the AGENTS.md / CLAUDE.md policy that tells agents to use Kage, auto-detects and wires your agents, and configures .gitignore + the packet merge driver. Requires Node.js 18+. No account, no API key.

Or just ask your agent to set it up. Paste this into Claude Code, Cursor, or any coding agent:

Set up Kage (verified memory for coding agents, https://github.com/kage-core/Kage)

in this repo: run npx -y @kage-core/kage-graph-mcp install, then tell me to restart you.

Other ways (plugin · per-agent · memory-only)

# Claude Code / Codex plugin

/plugin marketplace add kage-core/Kage # then: /plugin install kage@kage

wire a single agent (run `kage setup list` for all supported)

kage setup claude-code --project . --write

memory store only, no agent wiring

kage init --project .

confirm the harness is live

kage setup verify-agent --agent claude-code --project .

</details>

Delegate work (the orchestrator)

kage room --project .                      # talk to Kage; it briefs and hires agents for you

kage dispatch " " --agent claude # one delegated run, briefed from repo memory kage runs --project . # what every run is doing right now kage review --project . # read a finished run's claim and diff kage merge --project . # land the code and ratify what it learned

Every run works in its own git worktree. The checks that decide the verdict on the receipt above — tests, diff size, citations — are commands Kage runs itself, never the agent's self-report.

The app. kage app --project starts (or reuses) the local daemon and opens the same room, runs board, and memory view in a UI. From a checkout, npm start --prefix shell runs it as a native window — a thin Electron shell with no HTML of its own, it just loads the daemon's own page — and npm run dmg --prefix shell builds a macOS .dmg (arm64 only; Windows/Linux packaging isn't built yet).
From your phone. The daemon can also bind to your machine's LAN address, gated by a pairing secret required on every request, reads included. Today that means setting "lan": true in .agent_memory/config.json by hand — there's no --lan flag or app toggle yet.
Add a project without a terminal. kage projects add --agent claude registers another repo the same way the app's "+" button does, then kage app --project opens it.

kage app --project <dir>

kage projects add --agent claude

Desktop app

A thin native shell (macOS, arm64 only) over the same daemon the CLI runs — dock presence, a global hotkey, native notifications. Download the latest .dmg from GitHub releases (look for a Kage- .dmg asset).

Unsigned builds show macOS's "unidentified developer" prompt on first launch — right-click the app in Finder and choose Open once. Once installed, it checks for updates on launch and every 4 hours and installs on restart; ad-hoc (unsigned) builds can't self-install and notify you instead, linking back to the releases page.

Prefer the CLI? The one-line install works everywhere the app doesn't need to:

npx -y @kage-core/kage-graph-mcp install

What is Kage

Kage is an orchestrator for coding agents, built on a memory layer. As your agent works, it captures what it learns (decisions, bug fixes, conventions, how the code fits together) as Open Knowledge Format (OKF) concept files committed in your repo under .agent_memory/. The next session (yours or a teammate's) starts already knowing it, instead of re-reading or re-asking.

Three things make it different from other memory tools:

It's collaborative. The knowledge one person (or their agent) figures out becomes the whole team's. Memory is shared through git, so a teammate's next session starts with what you just learned, not a blank slate.
It's standard & git-native. Memory is a conformant OKF bundle — plain Markdown in your repo, reviewed in the same PR as the code, readable by any OKF tool — not locked in one machine or a vendor's cloud. Your knowledge stays yours.
It's verified. Every memory cites the code it's about, and Kage checks those citations against your actual files at write time, at recall time, and when a diff changes the code. Memory that no longer matches the code is withheld, so the agent never acts on a stale claim.

Kage called it. Google standardized it.

From day one, Kage kept agent memory as plain files in your repo — no cloud, no database, no lock-in, while everyone else was building memory clouds. In June 2026, Google Cloud shipped the Open Knowledge Format: knowledge as Markdown in git, vendor-neutral, no account — the exact thesis Kage already ran on. So Kage adopted OKF as its standard, and supercharges it with the layer OKF deliberately leaves out:

Verification — OKF stores what you wrote down; Kage checks every concept against your real code and refuses hallucinated citations at write time.
Freshness — OKF has no notion of staleness; Kage catches drift the moment your code changes and withholds memory that's no longer true.
Code-grounding — a deterministic code graph anchors each concept to the exact symbols it describes — the layer OKF leaves to tooling.

The trust metadata rides in OKF-legal x-kage-* fields, so a Kage bundle stays 100% conformant and opens in any OKF consumer, including Google's own visualizer. OKF standardizes the store; Kage is the verification and freshness layer Google left out.

How it works

Once installed, it's ambient. You don't run anything by hand:

Recall before acting. At the start of a task (and the moment the agent opens a file), Kage surfaces the relevant verified memory for it. Stale or deleted memory is left out.
Capture as it works. Durable learnings become packets. A memory that cites a file which doesn't exist is rejected on the spot, so hallucinations never enter storage.
Stay honest as the code moves. When a diff changes code that a memory cites, that memory is flagged at commit/PR time (kage pr check) and withheld from recall until it's re-verified or replaced, so knowledge can't quietly rot.

Watch it happen in the local dashboard (kage viewer): packets, the memory↔code graph, trust gates, and live events stream in as the agent works. Wrap anything in … and it's never stored.

kage viewer: the memory engine underneath the orchestrator above — your team's decisions, runbooks, and bug fixes (purple), kept in the repo and linked to the code they are about (blue).

Why Kage

Most memory tools (claude-mem, agentmemory, mem0, Zep) store memory per-machine or in a cloud you don't own, and never re-check it against the code. Kage keeps it in your repo and verifies it, so it stays your team's and stays true as the code changes.

	Kage	claude-mem	mem0 / Zep
Automatic capture + session-start recall	✓	✓	via SDK
Hallucinated citations rejected at write time	✓	—	—
Stale memory withheld at recall (cited files deleted/changed, TTL, reported)	✓	—	—
Diff-time stale-catch, warned before the PR when your change breaks a memory	✓	—	—
Memory reviewed in git, same PR as the code (plain files, no DB)	✓	SQLite + cloud	hosted API
Codify memory into team `SKILL.md` files agents auto-load	✓ (`kage skills`)	—	—

| Cross-mach

Only the beginning is shown; read the rest in the repo

Kage

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Kage manages your memory and agents

Install

wire a single agent (run kage setup list for all supported)

memory store only, no agent wiring

confirm the harness is live

Delegate work (the orchestrator)

Desktop app

What is Kage

Kage called it. Google standardized it.

How it works

Why Kage

wire a single agent (run `kage setup list` for all supported)