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Glama

Safety-first context & orchestration engine for AI coding agents.

npm license: MIT node: >=18

Works with any MCP-compatible agent: Claude Code, Cursor, Windsurf, Zed, and more.


What is Kuma?

Kuma is an MCP (Model Context Protocol) server that acts as a pre-modification safety layer for AI coding agents. Before an agent touches your code, Kuma enforces a research and safety pipeline — like a pre-flight checklist for code changes.

The Problem: AI agents often modify code without understanding the full context — missing dependencies, breaking related features, or repeating past mistakes.

The Solution: Kuma is a shadow memory that injects "where is this file fragile and why is it written this way" right before the agent touches it:

  • 🪄 Auto-inject hooks — gotchas/decisions/history injected before every edit, zero extra steps

  • 🧠 Knowledge graph — SQLite-based derived cache (hash-verified, never stale)

  • 📝 Decision memory — ADR-style decision tracking across sessions

  • 📊 Kuma Studio — Visual dashboard for gotchas, decisions, and shadow-memory metrics


Related MCP server: Code Executor MCP Server

Quick Start

# Run with npx (zero setup)
npx -y @plumpslabs/kuma

# Or install globally
npm install -g @plumpslabs/kuma
kuma

Kuma auto-generates:

  • .kuma/init.md — Project-specific behavioral rules

  • .kuma/kuma.db — SQLite knowledge graph (WASM, zero native build)

  • .skills/ — Skill files for common patterns


Core Architecture: 3 Pipeline-Driven Tools

Kuma exposes 3 coarse-grained tools with 13 core actions — the full agent surface. Anything else (impact, navigate, changes, digest, drift, resume, mine, session, delete_node, clear, goal_progress, check, audit, security, gc, ast, validate, gotcha_staleness) was removed — not hidden, gone — so the agent never has to choose from 30+ options and there is no dead surface to maintain.

🧠 kuma_context — Context & Research

Action

Purpose

Impact

init

Lean project brief + restore session

🔴 Required first

research

5-step pipeline: cache → graph → scan → impact → decision

🔴 Required before edits

history

Why is this file written this way (cross-session trace)

🔴 High

flow

Read a recorded architecture flow

🔴 High

💾 kuma_memory — Decision & Knowledge

Action

Purpose

Impact

gotcha

Record bugs/quirks IMMEDIATELY

🔴 Exponential

arch_flow

Record architecture flow (max 5 core files)

🔴 Exponential

decision

Record ADR-style decision with rationale

🔴 Exponential

research_save

Save research findings to cache

🟡 Linear

search

Quick lookup of memory + knowledge graph

🟡 Linear

🛡️ kuma_safety — Safety & Verification

Action

Purpose

Impact

guard

Detect anti-patterns, drift, runaway loops

🔴 Required

verify

Auto-run scoped tests after edits

🔴 High

checkpoint

Labeled snapshot before risky work

🟡 Linear

rollback_label

Restore a labeled snapshot

🟡 Linear


Architecture

Kuma exposes exactly 3 coarse-grained tools — the agent picks an action, Kuma runs the internal workflow:

Tool

Core Actions

Purpose

kuma_context

init, research, history, flow

Load project context, understand unfamiliar code

kuma_memory

gotcha, decision, arch_flow, research_save, search

Persistent knowledge that saves future sessions

kuma_safety

guard, verify, checkpoint, rollback_label

Pre-risk check, post-edit verification, snapshot/restore

Everything else is an internal action — not exposed to the agent. The agent uses its own native tools for editing, searching, and execution — Kuma is memory & safety, not a code manager.

What Kuma Provides

  • Knowledge Graph — SQLite + FTS5 full-text search (derived cache)

  • Session Memory — track tool calls, recordings, and efficiency per session

  • Guard System — real-time monitoring with blocking warnings for anti-patterns

  • Shadow Injection — gotchas injected before edits via hooks (zero token waste when clean)

  • Kuma Studio — visual dashboard with graph, gotchas, and injection metrics

  • Checkpoint/Rollback — atomic snapshots before major refactors


Kuma Studio

Kuma Studio is a web-based dashboard for visualizing and managing your knowledge graph.

Features

  • 📊 Knowledge Graph — Interactive node-edge visualization with physics simulation

  • ⚠️ Gotchas — Known bugs and quirks with severity levels

  • ⚡ Efficiency — Session metrics, time saved, verification pass rates

  • 🪄 Injections — Shadow-memory metrics: injection count + time saved (24h)

  • 📈 Staleness — Detection of stale nodes with missing file references

Usage

# Start Kuma Studio
kuma studio

# Or via npx
npx -y @plumpslabs/kuma studio

Studio runs at http://localhost:3322 and provides:

  • Real-time graph visualization

  • Copy report functionality for activity analysis

  • Node detail modals with relations and gotchas

  • Search and filter capabilities

  • Physics-based graph layout with depth controls


Knowledge Graph Schema

Kuma builds a comprehensive knowledge graph with these node types:

Node Type

Description

feature

High-level module (e.g., Auth, Billing)

arch_flow

Architecture flow between files

gotcha

Known bug or quirk

decision

ADR-style decision with rationale

function

Function or method

class

Class definition

component

UI component

file

Source file

api_route

API endpoint

test

Test file

research

Research cache entry

Edge types include: contains, flows_through, owns, explains.


Safety Layer

Audit Trail

Every safety check is logged to the audit trail:

  • Tool name and parameters

  • Risk level (low/medium/high/critical)

  • Allowed/blocked decision

  • Duration and metadata


Workflow

A typical Kuma-powered session follows this flow:

1. INIT          → kuma_context({ action: 'init' })
                   Load project brief, restore session context

2. RESEARCH      → kuma_context({ action: 'research', scope: '<area>' })
                   5-step pipeline: cache → graph → impact → decision → safety

3. GUARD         → kuma_safety({ action: 'guard' })
                   Check for anti-patterns, drift, runaway loops

4. EDIT          → Agent modifies code (native tools)

5. RECORD        → kuma_memory({ action: 'gotcha' | 'arch_flow' | 'decision' })
                   Record what was learned for future sessions

6. VERIFY        → kuma_safety({ action: 'verify' })
                   Auto-run scoped tests + validation

7. CHECKPOINT    → kuma_safety({ action: 'checkpoint', label: 'post-<feature>' })
                   Snapshot once stable — restore with rollback_label if needed

Per-Project Context Model

Kuma stores all context locally in .kuma/:

.kuma/
├── kuma.db          # SQLite knowledge graph (WASM) — nodes, edges, research cache, changes
├── init.md          # Project behavioral rules (generated by `kuma init`)
├── memory.json      # Session state + metrics (auto)
├── auto-gotcha.json # Self-learning loop state (auto)
├── policy.yml       # OPTIONAL safety policy — only read if you create it
├── memories/        # Decision log markdown (decisions.md)
├── checkpoints/     # Atomic snapshots (label/ with kuma.db + files/)

Hooks are registered in .claude/settings.json (PreToolUse) — not stored under .kuma/.

Research cache is not a folder — it lives in the research_cache table inside kuma.db.

Key principle: Context is per-project, per-agent. No shared state between projects.


Why Kuma?

Problem

Without Kuma

With Kuma

Context

Agent forgets project-specific patterns

Knowledge graph persists across sessions

Safety

Agent may break critical code

Policy engine blocks risky operations

Impact

Agent doesn't know what's affected

Impact analysis traces dependencies

Coordination

Multiple agents conflict

Per-agent session state + audit trail avoid collisions

Memory

Agent repeats past mistakes

Decision memory + gotchas prevent loops

Reversibility

Hard to undo changes

Checkpoint snapshots + rollback_label

Staleness

Knowledge becomes outdated

Drift detection + gotcha staleness checks flag stale data


Installation

# Global install
npm install -g @plumpslabs/kuma

# Or use npx (no install needed)
npx -y @plumpslabs/kuma

# With pnpm
pnpm add -g @plumpslabs/kuma

Requirements

  • Node.js >= 18.0.0

  • No native dependencies (uses WASM for SQLite)


CLI Commands

# Start MCP server (default)
kuma

# Start Kuma Studio dashboard
kuma studio

# Initialize a project
kuma init

# Show version
kuma --version

# Show help
kuma --help

Configuration

MCP Client Configuration

Add to your MCP client config (e.g., Claude Desktop):

{
  "mcpServers": {
    "kuma": {
      "command": "npx",
      "args": ["-y", "@plumpslabs/kuma"]
    }
  }
}

Environment Variables

Variable

Description

Default

KUMA_DB_PATH

Custom database path

.kuma/kuma.db

KUMA_POLICY_PATH

Custom policy file

.kuma/policy.yml

KUMA_STUDIO_PORT

Studio server port

3322


Development

# Clone the repo
git clone https://github.com/plumpslabs/kuma.git
cd kuma

# Install dependencies
pnpm install

# Build
pnpm run build:all

# Run tests
pnpm test

# Start studio in dev mode
pnpm run studio:dev

Power Curve: What to Record

What to Record

When

Why

Impact

arch_flow

After tracing a complete flow

Saves 5-10 files next session

🔴 Exponential

gotcha

IMMEDIATELY when finding bugs

Prevents re-discovery

🔴 Exponential

decision

When choosing between options

Preserves rationale

🔴 Exponential

feature

When identifying a module

Creates owns edges to files

🔴 Exponential

research_save

After exploring an area

Creates search cache

🔴 Exponential

Function/class nodes

Skip

Agent can grep/glob

🟢 Skip

Import edges

Skip

Agent can read imports

🟢 Skip

Visual graph

Skip

For humans, not AI

🟢 Skip


License

MIT — use freely in personal and commercial projects.


Community


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Maintenance

Maintainers
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0dRelease cycle
54Releases (12mo)
Commit activity

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