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Kage

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Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded

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Описание

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

README

Kage

In June 2026 Google shipped OKF (Open Knowledge Format): a standard for keeping knowledge as plain Markdown concept files in your repo, vendor-neutral, no lock-in. It standardizes the store and stops there. Verification, freshness, and staleness are explicitly out of scope for v0.1. Kage is the framework that maintains it. It captures what your coding agents learn as a conformant OKF bundle in git, then keeps every concept honest against your real code: a memory whose cited code no longer exists is rejected at write time, and one that drifts when the code changes is flagged and withheld until it is re-verified. Deterministic, no LLM on the verdict path. No account, no database, no API key.

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

npm version downloads license no account Built on Google Open Knowledge Format

Website · Docs · Live viewer · npm

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


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 .

What is Kage

Kage is a memory layer for coding agents. 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 — hooks watch the session; you don't run anything by hand. Four paths make up the loop:

flowchart LR
    A[session events<br/>prompts · edits · commands] -->|prose observations,<br/>signal-scored| B[distill on session end<br/>gate ≥0.4 · dedupe]
    B -->|drafts born pending| C{grounded + fail→pass<br/>evidence?}
    C -->|yes| D[approved packet<br/>OKF markdown in git]
    C -->|no| E[pending inbox<br/>kage review]
    D --> F[fingerprints:<br/>file hash + code-symbol anchors]
    F -->|cited code changed| G[stale: withheld<br/>until evidence reverify]
    D -->|ranked recall| H[injected context:<br/>session start · each prompt · each file open]
    D -->|git push/pull| I[teammate's next session]

Write path (capture). Hooks turn the session into observations — your prompts, each edit as prose (the edit content is where fixes and conventions live), each command with its output. Every observation is signal-scored; machine noise hard-rejects to zero. On session end, distill --auto gates (≥0.4), dedupes, and writes drafts born pending — never approved by default. One thing lifts a draft to trusted recall automatically: it cites real files, duplicates nothing, contradicts nothing, and the session contains a fail→pass command pair — mechanical evidence a real fix happened. Explicit kage_learn writes are refused if the cited files don't exist; secrets are scanned out.

Trust path (verification). Every packet fingerprints what it cites: a whole-file hash plus anchors on the code symbols the memory actually names (real identifiers only, never prose words). Cited code edited → soft-stale, withheld from recall until re-verified with evidence (kage reverify --evidence — a bare re-stamp on changed code is refused). Cited file deleted → hard-stale, withheld, garbage-collected after 30 days. "Verified" is earned by an actual check, never granted at birth.

Read path (recall). Three injection moments: session start (policy + "previously…" digest), every prompt (top verified packets + graph facts for what you asked), and every file the agent opens or edits (packets citing that file). Ranking trusts evidence — lexical match first, a damped graph prior that can't outvote a title match, recency decay so aged change-logs sink, and code-graph identifier grounding so a query for someFunction finds the packet citing the file that defines it. Stale memory never appears; every serve increments a real usage counter.

Team path (git). The store is plain OKF markdown committed in the repo — a teammate's clone is the memory transfer. A merge driver auto-resolves packet collisions (newest content wins), and kage pr check gates merges: if your diff breaks what a memory claims, you hear about it before the PR lands.

One principle threads through all four: every number Kage shows is a count of a reproducible check — never an estimate.

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 <private>…</private> and it's never stored.

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-machine sync ✓ your own git remote their cloud their cloud
Account / API key required none cloud optional yes

Features

  • Truth Report. kage scan reads any repo in seconds and surfaces its highest-risk knowledge gaps: undocumented hot files, untested hot paths, complexity hotspots, unresolved code debt, and bus-factor-1 files, plus duplicate implementations, dead exports, and doc lies when they exist. Every finding cited to file:line. Zero setup, nothing generated, runs before you install anything.
  • Savings receipts. kage gains keeps a per-repo value ledger (tokens + $ the agent didn't have to re-spend), every number traceable to a logged event; the agent relays it after each recall.
  • Team skills. kage skills turns durable, verified procedures into .claude/skills/<name>/SKILL.md files agents auto-load, committed and shared, no cloud.
  • Personal memory & sync. kage learn --personal keeps cross-machine notes in ~/.kage/memory, recalled as a clearly separated lower-trust section and synced over your own git remote.
  • Self-healing session loop. Uncaptured sessions are auto-distilled into pending drafts you review; kage resume opens each session with a "previously…" digest; kage repair fixes broken packets and indexes in one command.

Benchmarks

  • LongMemEval-S retrieval: 96.17% R@5 / 98.72% R@10, zero dependencies.
  • Memory Correctness Under Change: 0% stale-served (memory whose code was deleted or changed is withheld), vs 100% for capture-everything stores.

Methodology, commands, and caveats: docs/BENCHMARKS.md. Every number above has a reproducible harness in this repo; claims without one don't ship.

Daily commands

kage recall "how do I run tests" --project .
kage verify --project .        # check citations against current code
kage pr check --project .      # stale-catch + graph freshness gate
kage gains --project .         # what Kage saved you
kage viewer --project .        # local dashboard
kage okf migrate --project .   # render memory as a Google OKF bundle

Full CLI and MCP reference: docs.

Storage

Everything lives in .agent_memory/: packets/ is durable repo memory (git-tracked JSON); graph/, code_graph/, structural/, and indexes/ are rebuildable with kage refresh; reports/ holds the value ledger and health reports. Capture scans for secrets and PII before writing.

Standard format — Open Knowledge Format (OKF). Kage's memory is an OKF bundle: plain Markdown concept files with YAML frontmatter, readable by any OKF consumer (including Google's visualizer). Run kage okf migrate to render the store as an OKF bundle under .agent_memory/okf/. Kage adds the lifecycle OKF leaves out — grounding, verification, and freshness — carried in OKF-legal x-kage-* fields, and can import any third-party OKF bundle. The round-trip is lossless. See OKF_STANDARD.md.

Development

cd mcp
npm install
npm test
npm run build

Contributing & community

Kage is built in the open and we'd love your help. Zero runtime dependencies, no account, no cloud — it's a friendly codebase to jump into.

By participating you agree to our Code of Conduct.

License

GPL-3.0-only. See LICENSE. Releases before the GPL switch were MIT.

from github.com/kage-core/Kage

Установка Kage

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/kage-core/Kage

FAQ

Kage MCP бесплатный?

Да, Kage MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Kage?

Нет, Kage работает без API-ключей и переменных окружения.

Kage — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Kage в Claude Desktop, Claude Code или Cursor?

Открой Kage на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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