kuma
Integrates ESLint for linting via the static_analysis tool, parsing output into structured results.
Provides tools for viewing commit history and diffs, and includes safety measures like blocking dangerous git commands such as git push --force.
Integrates with npm for package management detection in project conventions and blocks dangerous npm publish commands.
Supports pnpm via workspace detection in monorepo awareness features.
Integrates Prettier for code formatting checks via the static_analysis tool.
Integrates Ruff for Python linting via the static_analysis tool.
Runs TypeScript static analysis (type checking) via the static_analysis tool and provides LSP-based queries with regex fallback.
Supports Yarn via workspace detection in monorepo awareness features.
Safety-first context & orchestration engine for AI coding agents.
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 β like a pre-flight checklist for code changes.
The Problem: AI agents often modify code without understanding the full context β 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:
πͺ Auto-inject hooks β gotchas/decisions/history injected before every edit, zero extra steps
π§ Knowledge graph β SQLite-based derived cache (hash-verified, never stale)
π Decision memory β ADR-style decision tracking across sessions
π Kuma Studio β Visual dashboard for gotchas, decisions, and shadow-memory metrics
Related MCP server: repo-seatbelt
Quick Start
β‘ Universal 1-Liner (Auto-detects your IDE/Agent)
curl -fsSL https://raw.githubusercontent.com/plumpslabs/kuma/main/install.sh | bashπ§© Or Install as a Native Plugin
Claude Code Marketplace:
/plugin marketplace add plumpslabs/kuma /plugin install kuma@plumpslabs-kumaAntigravity CLI (AGY):
agy plugin add https://github.com/plumpslabs/kumaVia NPX (Zero Install):
npx @plumpslabs/kuma init --all
π See INSTALL.md for the complete provider matrix (Cursor, Windsurf, OpenCode, Copilot, Zed, Cline, Aider, etc.).
Core Architecture: 3 Pipeline-Driven Tools
Kuma exposes 3 coarse-grained tools with 15 core actions β 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 β not hidden, gone β so the agent never has to choose from 30+ options and there is no dead surface to maintain.
π§ kuma_context β Context & Research
Action | Purpose | Impact |
| Lean project brief + restore session + branch tracking | π΄ Required first |
| 5-step pipeline: cache β graph β scan β impact β decision | π΄ Required before edits |
| Monorepo package topology & workspace boundary mapping | π΄ High |
| Concept-level subsystem clusters with typed relationship verbs | π΄ High |
| Compressed AST code outline (85-93% token reduction) | π΄ High |
| Anti-duplication helper discovery before writing new code | π΄ High |
| Blast radius analysis with PageRank centrality scoring | π΄ High |
| Why is this file written this way (cross-session trace) | π΄ High |
| Read a recorded architecture flow | π΄ High |
πΎ kuma_memory β Decision & Knowledge
Action | Purpose | Impact |
| Record bugs/quirks + lifecycle ( | π΄ Exponential |
| Record architecture flow (max 5 core files) | π΄ Exponential |
| Record ADR-style decision with rationale | π΄ Exponential |
| Save research findings to cache | π‘ Linear |
| Quick lookup of memory + knowledge graph | π‘ Linear |
π‘οΈ kuma_safety β Safety & Verification
Action | Purpose | Impact |
| Detect anti-patterns, drift, runaway loops | π΄ Required |
| Post-edit blast radius & affected test targeting (<50ms static resolution) | π΄ High |
| Labeled snapshot before risky work | π‘ Linear |
| Restore a labeled snapshot | π‘ Linear |
Architecture
Kuma exposes exactly 3 coarse-grained tools β the agent picks an action, Kuma runs the internal workflow:
Tool | Core Actions | Purpose |
|
| Load project context, understand unfamiliar code |
|
| Persistent knowledge that saves future sessions |
|
| Pre-risk guard, post-edit blast radius verification, snapshot/restore |
Everything else is an internal action β not exposed to the agent. The agent uses its own native tools for editing, searching, and execution β Kuma is memory & safety, not a code manager.
What Kuma Provides
Knowledge Graph β SQLite + FTS5 full-text search (derived cache)
Session Memory β track tool calls, recordings, and efficiency per session
Guard System β real-time monitoring with blocking warnings for anti-patterns
Shadow Injection β gotchas injected before edits via hooks (zero token waste when clean)
Kuma Studio β visual dashboard with graph, gotchas, and injection metrics
Checkpoint/Rollback β atomic snapshots before major refactors
Kuma Studio
Kuma Studio is a streamlined, modular web dashboard for visualizing your codebase intelligence, gotchas shield, and workspace topology without visual clutter.
Features
π‘οΈ Gotcha Shield β Filter gotchas by status (
active,verified,resolved), severity, and copy workarounds in 1 clickπ Domain Sequence Flows β Linear architecture hops and execution sequences
π¦ Workspace & Blast Radius β Monorepo package dependency matrix and real-time blast radius impact simulator
β‘ Health & Efficiency β Session metrics, estimated hours saved, verification pass rates, and injection statistics
πΈοΈ Calm Knowledge Graph β Clean node-link visualization with optional physics simulation and depth controls
Usage
# Start Kuma Studio
kuma studio
# Or via npx
npx -y @plumpslabs/kuma studioStudio 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 |
| High-level module (e.g., Auth, Billing) |
| Architecture flow between files |
| Known bug or quirk |
| ADR-style decision with rationale |
| Function or method |
| Class definition |
| UI component |
| Source file |
| API endpoint |
| Test file |
| 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 β kuma_context({ action: 'init' })
Load project brief, restore session context
2. RESEARCH β kuma_context({ action: 'research', scope: '<area>' })
5-step pipeline: cache β graph β impact β decision β safety
3. GUARD β kuma_safety({ action: 'guard' })
Check for anti-patterns, drift, runaway loops
4. EDIT β Agent modifies code (native tools)
5. RECORD β kuma_memory({ action: 'gotcha' | 'arch_flow' | 'decision' })
Record what was learned for future sessions
6. VERIFY β kuma_safety({ action: 'verify' })
Auto-run scoped tests + validation
7. CHECKPOINT β kuma_safety({ action: 'checkpoint', label: 'post-<feature>' })
Snapshot once stable β restore with rollback_label if neededPer-Project Context Model
Kuma stores all context locally in .kuma/:
.kuma/
βββ kuma.db # SQLite knowledge graph (WASM) β nodes, edges, research cache, changes
βββ init.md # Project behavioral rules (generated by `kuma init`)
βββ memory.json # Session state + metrics (auto)
βββ auto-gotcha.json # Self-learning loop state (auto)
βββ policy.yml # OPTIONAL safety policy β only read if you create it
βββ memories/ # Decision log markdown (decisions.md)
βββ checkpoints/ # Atomic snapshots (label/ with kuma.db + files/)Hooks are registered in
.claude/settings.json(PreToolUse) β not stored under.kuma/.
Research cache is not a folder β it lives in the
research_cachetable insidekuma.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/kumaRequirements
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 --helpConfiguration
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 |
| Custom database path |
|
| Custom policy file |
|
| Studio server port |
|
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:devPower Curve: What to Record
What to Record | When | Why | Impact |
| After tracing a complete flow | Saves 5-10 files next session | π΄ Exponential |
| IMMEDIATELY when finding bugs | Prevents re-discovery | π΄ Exponential |
| When choosing between options | Preserves rationale | π΄ Exponential |
| When identifying a module | Creates owns edges to files | π΄ Exponential |
| After exploring an area | Creates search cache | π΄ Exponential |
Function/class nodes | Skip | Agent can grep/glob | π’ Skip |
Import edges | Skip | Agent can read imports | π’ Skip |
Visual graph | Skip | For humans, not AI | π’ Skip |
License
MIT β use freely in personal and commercial projects.
Community
GitHub: github.com/plumpslabs/kuma
Available Tools
6 toolskuma_contextA
Context & memory recall. Call FIRST each session. Lean β each call returns only what you need.
CORE ACTIONS (use these): init (start of session: project brief + session state), research (before editing unfamiliar code), history (why is this file written this way), flow (read a recorded architecture flow), map (repository topology), impact (blast radius analysis), cluster (concept-level subsystem nodes), skeleton (compressed AST outline omitting bodies), reuse (discover existing helpers before writing duplicate code).
Inputs: action (required), goal, scope, target.
kuma_kuma_contextA
Context & memory recall. Call FIRST each session. Lean β each call returns only what you need.
CORE ACTIONS (use these): init (start of session: project brief + session state), research (before editing unfamiliar code), history (why is this file written this way), flow (read a recorded architecture flow), map (repository topology), impact (blast radius analysis), cluster (concept-level subsystem nodes), skeleton (compressed AST outline omitting bodies), reuse (discover existing helpers before writing duplicate code).
Inputs: action (required), goal, scope, target.
kuma_kuma_memoryA
Persistent knowledge. Record what matters, skip what doesn't. This is what saves time in future sessions. Don't record what grep/glob answers faster (functions, imports, types, components).
CORE ACTIONS (use these): gotcha (IMMEDIATELY when you find a bug/quirk), decision (when choosing between options), arch_flow (after tracing a complete flow, max 5 core files), research_save (after exploring an area), search (quick lookup of memory + knowledge graph), gotcha_resolve (archive fixed bugs), test_outcome (record changed files + failed tests to train test selection).
Inputs: action (required), id, limit, query, +13 more.
kuma_kuma_safetyA
Safety & verification. Use at task boundaries, not on every edit.
CORE ACTIONS (use these): guard (before risky work: anti-patterns, drift, loops), verify (after edits: scoped tests + validation), checkpoint + rollback_label (the one rollback mechanism: snapshot before risky work, restore after), cost (cost-per-tool ledger).
Inputs: action (required), force, label, scope, +7 more.
kuma_memoryB
Persistent knowledge. Record what matters, skip what doesn't. This is what saves time in future sessions. Don't record what grep/glob answers faster (functions, imports, types, components).
CORE ACTIONS (use these): gotcha (IMMEDIATELY when you find a bug/quirk), decision (when choosing between options), arch_flow (after tracing a complete flow, max 5 core files), research_save (after exploring an area), search (quick lookup of memory + knowledge graph), gotcha_resolve (archive fixed bugs), test_outcome (record changed files + failed tests to train test selection).
Inputs: action (required), id, limit, query, +13 more.
kuma_safetyA
Safety & verification. Use at task boundaries, not on every edit.
CORE ACTIONS (use these): guard (before risky work: anti-patterns, drift, loops), verify (after edits: scoped tests + validation), checkpoint + rollback_label (the one rollback mechanism: snapshot before risky work, restore after), cost (cost-per-tool ledger).
Inputs: action (required), force, label, scope, +7 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogβ¦
TDQS
Scored across 6 tools
The three functional groups (context, memory, safety) are reasonably distinct from each other, but each one is duplicated as an identical twin with a byte-for-byte identical description (kuma_context vs kuma_kuma_context, etc.). An agent has no basis to choose between a tool and its clone, guaranteeing arbitrary misselection in half the available surface.
Names follow a readable kuma_verb/noun snake_case pattern, but the redundant 'kuma_kuma_' prefix on three tools breaks the convention and looks like an accidental double-registration rather than a deliberate scheme. Consistent enough to parse, inconsistent enough to mislead.
Six tools would be a fine scope for this workflow, but three of them are exact duplicates, leaving only three effective tools covering context, memory, and safety. The apparent count overstates the real surface, though three genuine umbrellas is acceptable for the stated purpose.
Each umbrella tool exposes a rich action set (init/research/history/map/impact, gotcha/decision/search, guard/verify/checkpoint/rollback), covering the session lifecycle from recall through record to verification and rollback. Coverage looks solid; the main gap is that the duplicate twins add no capability, only noise.
Maintenance
Related MCP Connectors
AgentGuard β 20-tool AI safety MCP: policy preflight, risk scoring, audit logging, rate limits.
Safety tools for AI agents: safe page reader, prompt-injection, secrets, PII and MCP server scans
Memory, reflection and safety for AI agents. Hosted or local, no vector database.
Deterministic runtime safety for AI agents: scan PII, gate tool actions, verify LLM output.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceProvides sandboxed code execution for AI agents with support for Python, JavaScript, and shell commands. Includes comprehensive safety features like destructive pattern blocking, timeout protection, and restricted file access for secure production use.37 npm37 PyPIMIT
- AlicenseNot gradedqualityDmaintenanceRuntime safety guardrails for AI coding agents. Checks file access, validates shell commands, and scores your repo's AI safety β all via MCP.9 npm8MIT
- AlicenseNot gradedqualityDmaintenanceProvides AI agents with 25 security analysis tools including vulnerability scanning, package hallucination detection, prompt injection firewall, and CI/CD integration.1MIT
- AlicenseAqualityDmaintenanceAn MCP server that gives AI agents geometric spatial awareness of web page layouts using Playwright, enabling detection of visual occlusion, layout shifts, and spatial relationships.654 npmMIT