Crg

Better Code Review Graph

Renamed (2026-09-13): repo is now crg — CLI-first (crg command). PyPI package stays crg; MCP server is a secondary surface.

mcp-name: io.github.n24q02m/crg

Knowledge graph for token-efficient code reviews -- semantic search and call-graph resolution across your codebase.

[Mode] [CI] [codecov] [PyPI] [License: Apache-2.0]

[Python] [MCP] [semantic-release] [Renovate]

An MCP server that parses your codebase with Tree-sitter, builds a structural graph of functions/classes/imports, and gives Claude (or any MCP client) precise context so it reads only what matters instead of the whole tree. Semantic search runs through the local ONNX model registry from fastretrieval by default (zero config, no API key), with an optional cloud embedding chain. Fork of code-review-graph with fixed multi-word search, qualified call resolution, dual-mode embeddings, output pagination, and production CI/CD.

v2.0 migration (BREAKING)

v2.0 adds temporal columns (valid_from_sha / valid_to_sha on every node + edge) and an opt-in security scanner. The schema migration is auto-applied on first GraphStore open, and a backup of the pre-2.0 DB is saved to <graph_db>.pre-2.0.bak so you can roll back. See BREAKING_CHANGES.md for the full schema-change list, behavior changes, environment requirements, and the downgrade procedure (CRG_DOWNGRADE_TO_1_X=1 uv run crg).

Table of contents

• v2.0 migration (BREAKING)
• Install
• Usage
• Smithery
• Configuration
• Tools
• CLI
• Features
• Comparison
• Security
• Build from source
• Trust model
• Migration & changelog
• Documentation
• License

Install

For OMP and other local coding harnesses, the primary surface is the package CLI plus the bundled skills/ workflows. The skills invoke the CLI directly and do not require an MCP server mapping.

# Run without a persistent install (short `crg` script; PyPI package name stays# better-code-review-graph, so `uvx` needs the explicit --from form)uvx --python 3.13 --from better-code-review-graph crg graph build --full-rebuild \  --repo-root /path/to/repouvx --python 3.13 --from better-code-review-graph crg graph stats \  --repo-root /path/to/repo
# Or install the console scripts (installs both `crg` and the legacy long name)pip install better-code-review-graphcrg query search --search-query "authentication" \  --repo-root /path/to/repo

The optional Semgrep engine for deeper security scans is a separate extra:

pip install 'better-code-review-graph[security]'

MCP stdio remains a secondary protocol adapter for clients that require it:

{  "mcpServers": {    "crg": {      "command": "uvx",      "args": ["--python", "3.13", "better-code-review-graph"],      "env": { "MCP_TRANSPORT": "stdio" }    }  }}

Install matrix (stdio unless noted; the CLI-first usage above stays the primary surface):

Install with an AI agent -- paste this to your AI coding agent:

Install MCP server crg following the steps at https://raw.githubusercontent.com/n24q02m/claude-plugins/main/plugins/better-code-review-graph/setup-with-agent.md

Full CLI usage is in CLI. Optional per-client MCP setup is at mcp.n24q02m.com/servers/better-code-review-graph/setup/.

Usage

Two ways to run the server, plus the surfaces to consume it.

Dev: uv, no auth (loopback only)

# instance config lives at $CRG_CONFIG_DIR or ~/.crg (same schema as hull's# config.toml); a default no-auth template is fine for local devuv run better-code-review-graph server start# -> http://127.0.0.1:8000/mcp  (no-auth is refused on any off-loopback bind)

Always-on: docker (token auth)

cp docker-config/config.example.toml docker-config/config.toml# mint a token + hash (hull CLI ships with crg's dependency tree):#   TOKEN=$(python -c "import secrets; print(secrets.token_urlsafe(32))")#   hull token hash "$TOKEN"   # paste output into token_hash in config.tomldocker compose up -d

The compose file builds the Dockerfile's http target (image crg:http), publishes the container on host loopback only (127.0.0.1:${CRG_PORT:-8772}:8080), and mounts ./docker-config/config.toml read-only at the container's config dir (CRG_CONFIG_DIR=/data/config); graph state persists in the crg-data named volume. All state stays on your machine.

Consuming: CLI or MCP

CLI (local graphs, no server needed):

crg graph build --full-rebuild --repo-root /path/to/repocrg query search --search-query "authentication" --repo-root /path/to/repo

MCP over HTTP (remote/always-on): point any MCP client at http://127.0.0.1:8772/mcp with Authorization: Bearer <token>:

{  "mcpServers": {    "better-code-review-graph": {      "url": "http://127.0.0.1:8772/mcp",      "headers": { "Authorization": "Bearer <token>" }    }  }}

Per-task model configuration

Each task (embed / rerank / chat / jev_score) resolves its own OpenAI-spec provider cell from [models.<task>] in the instance config: an independent base_url + api_key + model. Cloud or local is purely a config choice — point base_url at OpenRouter, a vendor, or your own local gateway (e.g. http://host.docker.internal:11434/v1). API keys are host-only material: keep them in config.toml (gitignored under docker-config/) or supply via HULL_<TASK>_API_KEY env; they are never end-user supplied.

Local-first boundary

CRG is local-first for coding workflows:

• CLI and bundled Skills are the primary surfaces for graph build/query, impact analysis, review context, security scans, and repository onboarding.
• MCP stdio is the secondary protocol adapter over the same local domain services; it does not maintain a separate graph implementation.
• Graph state stays in <repo>/.crg/graph.db unless an explicit multi-user/self-host configuration selects another data directory.
• PyPI, CI, security scanning, GitHub releases, and eligible stable MCP Registry publication remain active. Historical public OCI tags are retained, but new public Docker Hub/GHCR images are no longer published.
• CRG has no hosted Cloudflare runtime in the target topology.

Smithery

The repo ships a smithery.yaml so the server can be built and run through Smithery. It deploys over stdio and needs no startup configuration -- the config schema is empty, and any optional cloud embedding/summary keys are supplied at runtime through the server's own config flow (see Configuration below). The launch command is the same uvx invocation as a local install:

startCommand:  type: stdio  commandFunction: |-    (config) => ({ command: 'uvx', args: ['--python', '3.13', 'crg'] })

Configuration

Everything works out of the box with zero configuration -- semantic search uses the local ONNX registry from fastretrieval (Qwen3-Embedding-0.6B is the current built-in reference entry, ~570 MB downloaded on first graph embed). This reference entry is not a Qwen-only boundary: any built-in registry ID or valid non-Qwen artifact manifest follows the same resolver. All environment variables below are optional and only needed for cloud embeddings, LLM summaries, or an explicit BYO local artifact.

Model selection

Embeddings select the first provider/model entry in EMBEDDING_MODELS; later entries are retained as configuration but are not runtime fallbacks. Summaries select the first SUMMARY_MODELS entry too, without runtime fallback. Providers are inferred from model prefixes and use the matching <PROVIDER>_API_KEY.

Cohere embed-v4.0 requests and stores 1024 dimensions; other backends retain 768-dimensional storage. CRG never slices, pads, or silently accepts a different provider width. The embedding row's model and byte width must match before reuse. Run graph(action="embed") after changing models or upgrading an old 768-wide Cohere index. Searches reject incompatible widths before a provider call; graph nodes are retained and re-embedding replaces only stale vectors.

Provider API keys

Cloud models need the provider key for the selected model prefix. Keys alone never select models: an empty embedding chain stays local, and an empty summary chain stays disabled. A configured cloud error does not fall back to local or another provider. Summarizers require a chat-completion model.

Advanced

When LOCAL_RERANK_MODEL is configured, semantic vector search retrieves a bounded candidate pool of min(max(limit * 4, limit), 100) rows, applies the existing kind, repo, and live-row filters, then reranks that pool and returns at most limit rows. The response uses search_mode="semantic_reranked" and adds rerank_score while preserving similarity_score. Blank keeps the existing limit * 2 vector path and search_mode="semantic". Configured reranker failures return an explicit error; CRG does not silently fall back to vector or keyword results. Keyword searches, including as_of snapshots, do not invoke the reranker.

Example -- cloud embeddings + summaries

{  "mcpServers": {    "crg": {      "command": "uvx",      "args": ["--python", "3.13", "better-code-review-graph"],      "env": {        "MCP_TRANSPORT": "stdio",        "EMBEDDING_MODELS": "cohere/embed-v4.0",        "SUMMARY_MODELS": "openrouter/minimax/minimax-m3:free",        "EMBEDDING_API_BASE": "https://gateway.ai.cloudflare.com/v1/<account>/<gateway>/cohere/v2/embed",        "LLM_API_BASE": "https://gateway.ai.cloudflare.com/v1/<account>/<gateway>/openrouter/v1",        "COHERE_API_KEY": "<cohere-key>",        "OPENROUTER_API_KEY": "<openrouter-key>"      }    }  }}

Cohere embedding is paid. Authorize a bounded budget before a live index/query; the Minimax-free completion choice does not make embeddings free. This example does not add a process-wide model override: missing subject credentials fail closed rather than inheriting the server environment.

CRG currently has no cloud rerank call: LOCAL_RERANK_MODEL is its only reranking path. Setting RERANK_MODELS or RERANK_API_BASE does not enable one.

Tools

Six tools, each grouping related actions to keep the tool surface small.

graph -- Graph lifecycle

Actions: build | update | stats | embed | export | summarize

query -- Graph queries

Actions: query | search | impact | large_functions | spot_check | renamed_in_diff | diff

Most read actions accept as_of=<sha> for temporal (point-in-time) snapshots and repo=<repo_id> to scope a federated multi-repo graph.

review -- Code review context

Actions: context (default) | delta

Token-optimized review context with structural summary, impacted nodes, source snippets, and review guidance. context auto-detects changed files from the git diff; delta (with from_sha/to_sha, optional show_line_shifts) surfaces refactor moves between two commits.

config -- Server configuration and credential setup

Actions: status | set | cache_clear | setup_status | setup_start | setup_skip | setup_reset | setup_complete

security -- Security scanning

Actions: scan | report | suppress | rule_list

The semgrep engine requires the [security] extra and runs Semgrep's p/auto registry pack plus a 3-rule curated overlay.

help -- Full documentation

Topics: graph | query | review | config | security | recipes

Returns complete documentation for each tool. Use when the compressed descriptions above are insufficient.

CLI

The package installs two console scripts: crg (primary) and crg (legacy long name). Running either with no arguments starts the MCP server over stdio; a leading positional argument routes to a local CLI subcommand that calls the same domain services used by the MCP adapter. Run them directly after pip install, or without a persistent install via uvx --python 3.13 --from better-code-review-graph crg ....

# Start the MCP server over stdio (default -- no subcommand)crg
# Build, inspect, and embed the local graphcrg graph buildcrg graph statscrg graph embed
# Query relationships and impactcrg query query \  --pattern callers_of --target "path/to/module.py::function"crg query search --search-query "authentication"crg query impact --changed-files src/app.py
# Produce review context and run a local security scancrg review context --base HEAD~1crg security scan --engine heuristic

CLI subcommands print structured JSON and exit non-zero on an error.

Features

What this fork fixes versus the upstream code-review-graph:

Comparison

How crg stacks up against direct competitors in each pillar:

Sources: Greptile · Greptile pricing · Sourcegraph MCP · CodeGraph. Cells marked ? are capabilities the competitor does not publicly document, not confirmed absences.

Security

• Explicit selection -- Cloud embedding errors are reported; the runtime does not silently switch models or fall back to local ONNX.
• Error handling -- Tools return error strings with fix suggestions, never crash.
• Read-only mount -- Docker mode mounts the repo as :ro (read-only).
• SSRF-guarded endpoints -- Custom EMBEDDING_API_BASE / LLM_API_BASE URLs are validated before any outbound call.

To report a vulnerability, see SECURITY.md.

Build from source

git clone https://github.com/n24q02m/crgcd crguv sync --group devuv run pytestuv run crg

Requirements: Python 3.13, uv.

Trust model

This plugin implements TC-Local (machine-bound, single trust principal). See the mcp-core trust model for full classification.

Migration & changelog

Graph, security scan cache, and suppression state now use the package-owned .crg/ directory. Run graph(action="build", full_rebuild=true) once after upgrading, followed by graph(action="embed") if semantic search is needed. The old .better-code-review-graph/ state directory plus the ambiguous .code-review-graph/ and .code-review-graph.db paths and their SQLite sidecars are left untouched, not migrated. Review and reapply any desired suppression rules explicitly.

The v2.0 release added temporal columns (valid_from_sha / valid_to_sha on every node and edge) plus an opt-in security scanner. The schema migration is auto-applied on first GraphStore open, and a backup of the pre-2.0 DB is written to <graph_db>.pre-2.0.bak. To downgrade and restore it:

CRG_DOWNGRADE_TO_1_X=1 uvx better-code-review-graph

Full schema-change list, behavior changes, and rollback procedure: BREAKING_CHANGES.md. Release-by-release history: CHANGELOG.md.

Documentation

Full docs at mcp.n24q02m.com/servers/better-code-review-graph/setup/:

• Setup -- install methods for Claude Code, Codex, Gemini CLI, Cursor, Windsurf, mcp.json
• Modes overview -- stdio / local-relay / remote-relay / remote-oauth
• Multi-user setup -- per-JWT-sub credential model

Use the help tool from any MCP client for inline per-tool reference.

License

Apache-2.0 -- See LICENSE.