LeanKG

by FreePeakVerified

LeanKG: Stop Burning Tokens. Start Coding Lean.

212
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26
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Rust
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8/23/2026
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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillTip is an informational directory and does not control or maintain the underlying repository. Any security checks displayed are automated and limited in scope. Review the source code before installing.

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Installation

Add to your Claude Code skills directory:

# Add to your Claude Code skills
git clone https://github.com/FreePeak/LeanKG

Getting Started

Guides for using skills like LeanKG.

Security Report

Verified

Last scanned: —

{
  "status": "PASSED",
  "issues": []
}

README.md

LeanKG

LeanKG

Enterprise-ready code knowledge graph for AI coding agents
Multi-repo · env governance · incidents & services · req↔code · −65% tokens / −85% tool calls

Live Demo · Docs · Docker Hub

License: Apache 2.0 crates.io Docker Hub CI

LeanKG


Installation

Prerequisites

Postgres + pgvector is required (only storage engine). From a LeanKG checkout:

docker compose up -d postgres   # host :5433

Default URL: postgresql://postgres:postgres@localhost:5433/leankg (override with LEANKG_PG_URL).
One-liners below do not start Postgres — they fail if :5433 is down.

One-liners

# Docker — index + embed + MCP HTTP (Postgres must already be up)
curl -fsSL https://raw.githubusercontent.com/FreePeak/LeanKG/main/scripts/docker-up.sh | bash

# Agent — binary + MCP wiring (cursor | claude | opencode | gemini | kilo | antigravity | docker | update)
curl -fsSL https://raw.githubusercontent.com/FreePeak/LeanKG/main/scripts/install.sh | bash -s -- cursor

Skip cold embed: LEANKG_SKIP_EMBED=1 curl -fsSL …/docker-up.sh | bash

Docker (manual)

docker compose up -d          # Postgres :5433 + MCP :9699
# or MCP only (bring your own PG via LEANKG_PG_URL):
docker run -d --name leankg -p 9699:9699 \
  -e LEANKG_PG_URL=postgresql://postgres:postgres@host.docker.internal:5433/leankg \
  -v "$(pwd):/workspace" freepeak/leankg:latest
curl http://localhost:9699/health

MCP URL: http://localhost:9699/mcp

From source

cargo install leankg
# or: git clone https://github.com/FreePeak/LeanKG.git && cd LeanKG && cargo build --release

Get Started

# 0. Postgres once — point at your instance (or: docker compose up -d postgres)
export LEANKG_PG_URL="postgres://user:pass@host:5432/db"

# 1. Per project: init -> migrate -> index
cd your-project
leankg init && leankg migrate && leankg index ./src

# 2a. Wire up an AI client — one command (also: cursor | codex | gemini)
leankg connect claude-code           # add --remote http://host:9699 to reuse a shared server

# 2b. ...or serve MCP over HTTP yourself
leankg mcp-http --port 9699          # GET /health returns 200 when ready

Self-check any deployment: leankg doctor --deep — PG latency, migrations, index freshness, embedding coverage, pool env, orphan edges, duplicate names (exit 0 pass / 1 warn / 2 fail).

Measured timings (scripts/quickstart_smoke.sh, run weekly in CI): full e2e smoke 88 s vs a 300 s budget; indexing a small repo takes well under 2 minutes.

Docker MCP users: pass container paths as project= (e.g. /workspace), never host paths.

Server-side setup pipeline (clone -> index -> embed)

leankg setup with no flags keeps the legacy client-side behavior (register MCP + hooks). Pass pipeline flags to instead clone a list of repos and index each one server-side:

# Status: print the resolved repo list without running anything
LEANKG_REPOS="github.com/org/repo-a,github.com/org/repo-b" leankg setup --status

# Clone + index + embed each repo under LEANKG_CLONE_ROOT (default: cwd)
LEANKG_REPOS="github.com/org/repo-a,github.com/org/repo-b" \
  LEANKG_GIT_REF=main \
  LEANKG_CLONE_ROOT=/srv/repos \
  leankg setup --clone --index --embed

Repo sources:

  • LEANKG_REPOS — comma-separated host/namespace paths to clone.
  • LEANKG_PROJECT_DIRS — comma-separated dirs already mounted on disk (skips clone; falls back to indexing what exists when no git token is set).

Env knobs: LEANKG_GIT_HOST (default github.com), LEANKG_GIT_REF (default main), LEANKG_CLONE_ROOT / CLONE_ROOT, LEANKG_ENV (default local), git token via GITLAB_TOKEN / GIT_TOKEN / GITHUB_TOKEN. Each cloned repo gets a minimal .leankg/leankg.yaml, then leankg index and leankg embed --wait run inside it. A setup.done marker prevents re-runs.

Set LEANKG_SETUP=1 on leankg mcp-http to run the same pipeline once after the server binds (spawned as a background task; the server stays healthy).

Web UI

UI talks REST (:8080), not MCP (:9699). Start the API, then the Vite app in ui-v2/:

# Terminal A — REST API (+ embedded UI if assets are in src/embed/)
leankg serve --port 8080
# open http://127.0.0.1:8080/

# Terminal B — hot-reload explorer (recommended for local UI work)
cd ui-v2
npm install
npm run dev
# open http://127.0.0.1:5173/?path=src

Vite proxies /api127.0.0.1:8080. Status should show connected.
Details: ui-v2/README.md · docs/web-ui.md


Enterprise Ready

Peers in this space are mostly personal / single-repo. LeanKG is the company platform: shared index, ops graph, and measured agent economics.

PillarShips as
Multi-repo serverDocker MCP :9699 + Postgres/pgvector; LEANKG_PROJECT_DIRS
Env governanceenv=, promote_environment, find_env_conflicts
Ops & ownershipget_service_graph, query_incidents, get_team_map
Req ↔ codeindex_prd, get_traceability, get_traceability_matrix
Mega-graphFrontier-local queries; 100k–700k+ elements
Agent surface85+ MCP tools (peers typically ~1–17)
CostA/B −65% tokens, −85% tool calls, 2.5× vs grep/cat
CapabilityLeanKGGitNexusGraphifyCodannaContext7
Multi-repo team deployYesPartialLimitedLimitedn/a
Env / incidents / team mapYesNoNoNoNo
PRD traceabilityYesNoPartialNoNo
Mega-graph (100k+)YesPartialViz cappedVariesn/a
MCP depth85+~17~10~5docs only

Deep dives: ROI vs Graphify · Competitive one-pager · Research matrix


Why LeanKG?

Agents normally rebuild structure with grep → open files → huge context. LeanKG returns a targeted subgraph (callers, dependents, blast radius, tests, docs) plus the team layer (env, services, incidents, requirements) over MCP.

WithoutWith LeanKG
Many tool calls, large contextSurgical subgraph + TOON (~40% smaller payloads)
No blast radiusSeverity-graded impact
Keyword onlyKeyword + HNSW semantic + ontology
Single-repo guessworkMulti-repo index + ops tools

Key Features

  • MCP-native — search, impact, call graphs, ontology, architecture, team knowledge
  • Postgres + pgvector — only storage engine; HNSW semantic search (--features embeddings / Docker)
  • Procedural ontology — hot-reload ontology/workflows.yamlkg_trace_workflow
  • Impact & depsimports, calls, tested_by, http_calls, service_calls
  • Web UI v2 — Force / Tree / Circles explorer (leankg serve + cd ui-v2 && npm run dev)
  • Languages — Rust, Go, C/C++, Java, Kotlin, TS/JS, Python, Ruby*, PHP*, Dart, Swift*, ObjC*, Terraform, CI YAML (*depth varies)

MCP prefer-order

Discover first — do not open with query_graph:

get_overview_contextmcp_statusconcept_searchsemantic_searchsearch_code / find_function → impact / deps / get_context

QuestionFirst tools
Fuzzy / domain NLconcept_searchsemantic_searchsearch_code
Exact symbol / filefind_function / search_code / query_file
How A↔B?shortest_path
Expand after seedsquery_graph

Catalog: docs/mcp-tools.md · Setup: docs/agentic-instructions.md


CLI

leankg init | index ./src | status | update
leankg impact <file> --depth 3
leankg path <from> <to> | explain <symbol> | graph-query "<q>"
leankg embed --init && leankg embed   # --features embeddings
leankg mcp-stdio --watch | mcp-http --port 9699 | serve --port 8080
leankg ontology sync | ontology trace <workflow>

UI hot-reload: cd ui-v2 && npm install && npm run devhttp://127.0.0.1:5173

Full reference: docs/cli-reference.md


Docs

Doc
ArchitectureDesign & data model
MCP toolsTool catalog
CLIAll commands
BenchmarksMethodology
EmbeddingsHNSW / ops
Postgres migrationEngine notes
AGENTS.mdAgent / Docker notes

Troubleshooting

IssueFix
High RAM (macOS)LEANKG_MMAP_SIZE=134217728 — see INSTRUCTION.md
MCP “not initialized” in DockerUse container project=/workspace, not the host path
Embeddings / cold embedsrc/embeddings/EMBEDDINGS.md

Requirements: macOS or Linux · Docker recommended for teams · Rust 1.75+ only when building from source.


Contributing

  1. Fork + feature branch (prefer a worktree)
  2. Update docs when behavior changes
  3. cargo build --release && cargo test
  4. Open a PR with summary + test plan

License

Apache License 2.0

Frequently Asked Questions

What is LeanKG?

LeanKG is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by FreePeak. LeanKG: Stop Burning Tokens. Start Coding Lean. It has 212 GitHub stars.

Is LeanKG safe to use?

Yes. LeanKG passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install LeanKG?

Clone the repository with "git clone https://github.com/FreePeak/LeanKG" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is LeanKG written in?

LeanKG is primarily written in Rust. It is open-source under FreePeak on GitHub, so you can review or fork the full source.

Are there alternatives to LeanKG?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh LeanKG against similar tools.

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