n24q02m

Better Code Review Graph

Community n24q02m
Updated

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

Better Code Review Graph

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

mcp-name: io.github.n24q02m/better-code-review-graph

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

ModeCIcodecovPyPILicense: Apache-2.0

PythonMCPsemantic-releaseRenovate

Sister projects from n24q02m (click to expand)
Project Tagline Tag
agent-chat-plugin Peer AI agents chat in a shared folder — no human relay, no orchestrator, wor... Tooling
better-code-review-graph Knowledge graph for token-efficient code reviews -- semantic search and call-... MCP
better-drive 2-way Google Drive sync with .driveignore filter — rclone engine, Windows tray Tooling
better-email-mcp IMAP/SMTP email for AI agents -- read, send, organize folders, and manage att... MCP
better-godot-mcp Composite MCP server for Godot Engine -- 17 composite tools for AI-assisted g... MCP
better-notion-mcp Markdown-first Notion for AI agents -- pages, databases, blocks, and comments... MCP
better-semantic-release Drop-in python-semantic-release fork with built-in release-safety guards (orp... Tooling
better-telegram-mcp Telegram for AI agents -- messages, chats, media, and contacts across both bo... MCP
better-workspace-mcp Google Workspace MCP server (Docs/Drive/Calendar/Gmail/Sheets/Slides/Tasks/Ch... MCP
claude-plugins Claude Code plugin marketplace for the n24q02m MCP servers -- install web sea... Marketplace
imagine-mcp Image and video understanding + generation for AI agents -- across Gemini, Op... MCP
jules-task-archiver Chrome Extension for bulk operations on Jules tasks via batchexecute API -- a... Tooling
mcp-core Shared foundation for building MCP servers -- Streamable HTTP transport, OAut... MCP
mnemo-mcp Persistent AI memory with hybrid search and embedded sync. Open, free, unlimi... MCP
fastretrieval Fast multi-model retrieval runtime for ONNX and GGUF embeddings, reranking, and model contracts Library
skret Secrets without the server. CLI
tacet A self-distilling neuro-symbolic cascade that amortises LLM cost across knowl... Tooling
web-core Shared web infrastructure package for search, scraping, HTTP security, and st... Library
wet-mcp Open-source MCP server for AI agents: web search, content extraction, and lib... MCP

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 better-code-review-graph).

Table of contents

  • v2.0 migration (BREAKING)
  • Install
  • 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 CLIplus the bundled skills/ workflows. The skills invoke the CLI directly and donot 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/repo
uvx --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-graph
crg 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": {
    "better-code-review-graph": {
      "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):

Client Install
Claude Code (plugin) /plugin marketplace add n24q02m/claude-plugins then /plugin install better-code-review-graph@n24q02m-plugins
Claude Code (stdio) claude mcp add better-code-review-graph -- uvx --python 3.13 better-code-review-graph
Codex register stdio command uvx --python 3.13 better-code-review-graph under mcp_servers in ~/.codex/config.toml
Gemini CLI add the mcpServers JSON above to ~/.gemini/settings.json
Cursor / Windsurf add the mcpServers JSON above via the client's MCP settings (mcp.json)
Any client (HTTP self-host) point the client at https://<your-host>/mcp (MCP_TRANSPORT=http) -- self-host only, no hosted endpoint

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

Install MCP server better-code-review-graph following the steps athttps://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 atmcp.n24q02m.com/servers/better-code-review-graph/setup/.

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 domainservices; it does not maintain a separate graph implementation.
  • Graph state stays in <repo>/.better-code-review-graph/graph.db unless an explicitmulti-user/self-host configuration selects another data directory.
  • PyPI, CI, security scanning, GitHub releases, and eligible stable MCP Registrypublication remain active. Historical public OCI tags are retained, but newpublic 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 andrun through Smithery. It deploys over stdio and needsno startup configuration -- the config schema is empty, and any optional cloudembedding/summary keys are supplied at runtime through the server's own configflow (see Configuration below). The launch command is the sameuvx invocation as a local install:

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

Configuration

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

Model selection

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

Variable Purpose Empty (default)
EMBEDDING_MODELS Cloud embedding selection; the first entry is active Local fastretrieval registry
SUMMARY_MODELS Completion model selection for graph(action="summarize") Summaries disabled

Cohere embed-v4.0 requests and stores 1024 dimensions; other backends retain768-dimensional storage. CRG never slices, pads, or silently accepts a differentprovider 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-wideCohere index. Searches reject incompatible widths before a provider call; graphnodes are retained and re-embedding replaces only stale vectors.

Provider API keys

Cloud models need the provider key for the selected model prefix. Keys alonenever select models: an empty embedding chain stays local, and an empty summarychain stays disabled. A configured cloud error does not fall back to local oranother provider. Summarizers require a chat-completion model.

Model prefix API key env var Get a key
jina_ai/ JINA_AI_API_KEY https://jina.ai/api-key
gemini/ GEMINI_API_KEY (or GOOGLE_API_KEY) https://aistudio.google.com/apikey
openai/ (or bare text-embedding-*) OPENAI_API_KEY https://platform.openai.com/api-keys
cohere/ COHERE_API_KEY https://dashboard.cohere.com/api-keys
openrouter/ OPENROUTER_API_KEY https://openrouter.ai/settings/keys
vertex_express/ GOOGLE_VERTEX_EXPRESS_API_KEY https://cloud.google.com/vertex-ai/generative-ai/docs/start/express-mode/overview

Any other litellm provider works viaits standard <PROVIDER>_API_KEY.

Advanced

Variable Purpose
EMBEDDING_API_BASE Provider-compatible endpoint for cloud embedding, including CF AI Gateway (SSRF-guarded)
LLM_API_BASE Provider-compatible base URL for the summarizer, including CF AI Gateway (SSRF-guarded)
DISABLE_LOCAL_EMBED Skip the local ONNX download; embedding is unavailable unless a cloud chain is configured
LOCAL_EMBEDDING_MODEL Built-in fastretrieval model ID, or a local directory containing fastretrieval-manifest.json
LOCAL_RERANK_MODEL Fastretrieval TextCrossEncoder model ID for bounded semantic reranking
LOCAL_EMBEDDING_DIM Required dimension for an external model ID without a manifest
LOCAL_EMBEDDING_MODEL_FILE ONNX file path inside a manifest-backed artifact directory
LOCAL_EMBEDDING_POOLING Explicit pooling for an external ID without a manifest: CLS, MEAN, LAST_TOKEN, or DISABLED
LOCAL_EMBEDDING_NORMALIZE Explicit L2 normalization for an external ID without a manifest
CRG_DATA_DIR Override the per-user data directory (default ~/.crg) used for per-user graphs and credentials in HTTP multi-user mode
EMBEDDING_BACKEND / EMBEDDING_MODEL / SUMMARY_MODEL Deprecated singular vars, honored one release with a warning -- migrate to the *_MODELS chains

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

Example -- cloud embeddings + summaries

{
  "mcpServers": {
    "better-code-review-graph": {
      "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 exampledoes not add a process-wide model override: in remote mode each authenticatedsubject's relay record supplies its models, endpoints and keys. Missing subjectcredentials fail closed rather than inheriting the server environment.

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

You can also configure cloud keys interactively in HTTP mode via the relaysetup form (config(action="setup_start") returns the browser URL). See themodes overview andmulti-user setup.

Workspace username (HTTP setup form)

The relay setup form has an optional workspace username field. Entering thesame username always lands you in the same per-sub bucket, so your keys andgraph stay reachable across a re-authorization and across devices, instead ofbeing tied to the one-off subject minted for each /authorize round-trip.Leaving it blank keeps the previous per-authorize behaviour.

Trust boundary: when the form is gated by a shared MCP_RELAY_PASSWORD, theusername is a partition key, not a secret -- anyone who knows that password cantype any username and reach that bucket. That is fine for a trusted group; anuntrusted multi-tenant deployment needs a per-user secret or delegated OAuthinstead.

One-time migration: existing users must re-enter their credentials once afterthis change. Nothing is deleted; credentials stored under the old random subjectare simply no longer addressed.

Tools

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

graph -- Graph lifecycle

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

Action Description
build Full or incremental graph build. Set full_rebuild=true to re-parse all files; pass roots to federate extra repo directories into one graph.
update Alias for build with full_rebuild=false (incremental).
stats Graph size, languages, node/edge breakdown, embedding count.
embed Compute vector embeddings for semantic search. Dual-mode: local ONNX or cloud chain.
export Export the graph as graphml / json-ld / dot / cypher. Inline or to output_path.
summarize LLM-generated one-paragraph docstrings for Function nodes (via the first explicit SUMMARY_MODELS entry; no-op when no model is selected). Calls bounded by max_nodes.

query -- Graph queries

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

Action Description
query Predefined patterns: callers_of, callees_of, imports_of, importers_of, children_of, tests_for, inheritors_of, file_summary.
search Search code entities by name/keyword or semantic similarity.
impact Blast radius of changed files. Auto-detects from git diff. Paginated with max_results.
large_functions Find functions/classes exceeding a line-count threshold.
spot_check Random callsite snippets from the last callers_of/callees_of/inheritors_of/importers_of result.
renamed_in_diff Symbols whose callsite line shifted versus a base ref.
diff Nodes added/removed/modified between two commit SHAs (from_sha, to_sha).

Most read actions accept as_of=<sha> for temporal (point-in-time) snapshotsand 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, sourcesnippets, and review guidance. context auto-detects changed files from thegit 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

Action Description
status Server info: version, graph path, node/edge counts, embedding backend, embeddings count.
set Update a runtime setting (key=log_level).
cache_clear Remove all computed embeddings.
setup_status Show current credential state, providers configured, and setup URL.
setup_start Start relay setup to configure API keys via browser (HTTP mode).
setup_skip Set local mode (skip relay permanently, use ONNX only).
setup_reset Clear credentials and reset state.
setup_complete Re-resolve credentials from environment variables.

security -- Security scanning

Actions: scan | report | suppress | rule_list

Action Description
scan Run a security scan (engine='heuristic' default = 5 regex rules, or 'semgrep'). Findings persist on nodes.security_tags.
report Re-emit cached findings as JSON (format='json') or SARIF v2.1.0 (format='sarif').
suppress Suppress a finding by rule_id (or remove=true to un-suppress).
rule_list List available rules for an engine.

The semgrep engine requires the [security] extra and runs Semgrep'sp/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 compresseddescriptions above are insufficient.

config__open_relay -- Re-trigger the relay setup form

Registered automatically from mcp-core.In HTTP mode it returns <PUBLIC_URL>/authorize so the agent can re-open thebrowser setup form (e.g. after credential expiry); in stdio mode it returnsstatus: 'stdio_unsupported'.

CLI

The package installs two console scripts: crg (primary) andbetter-code-review-graph (legacy long name). Running either with noarguments starts the MCP server over stdio; a leading positional argumentroutes to a local CLI subcommand that calls the same domain services used bythe MCP adapter. Run them directly after pip install, or without apersistent 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 graph
crg graph build
crg graph stats
crg graph embed

# Query relationships and impact
crg 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 scan
crg review context --base HEAD~1
crg security scan --engine heuristic
Command Description
graph build Full or incremental graph build. --full-rebuild re-parses every file; --base <ref> sets the incremental diff ref; --repo-root <path> overrides auto-detection.
graph embed Compute vector embeddings using local ONNX or the configured cloud chain.
graph stats / graph export / graph import / graph summarize Inspect, export/import a portable crg graph, or summarize functions.
query query / query search Run relationship patterns or keyword/semantic search.
query impact / query large_functions Analyze changed-file blast radius or find oversized nodes.
query spot_check / query renamed_in_diff / query diff Inspect callsites, line shifts, or commit-to-commit graph changes.
review context / review delta Generate review context or diff buckets for a code change.
security scan / security report / security suppress / security rule_list Run and manage heuristic/Semgrep security findings.
config status / config delete Show or remove stored credential config (--yes skips confirmation).
doctor Environment self-check from shared mcp-core CLI.
relay status / relay open / relay reset Inspect, open, or clear the relay setup session.

CLI subcommands print structured JSON and exit non-zero on an error. Theconfig, doctor, and relay subcommands come from shared mcp-core.

Features

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

Feature code-review-graph better-code-review-graph
Multi-word search Broken (literal substring) AND-logic word splitting
callers_of/callees_of Empty results (bare name targets) Qualified name resolution + bare fallback
Embedding sentence-transformers + torch (1.1 GB) fastretrieval ONNX + cloud (200 MB), dual-mode
Output size Unbounded (500K+ chars) Paginated (max_results, truncated flag)
Tool design 9 individual tools 7 grouped tools: graph + query + review + config + security + help + config__open_relay
Plugin hooks Invalid PostEdit/PostGit Valid PostToolUse

Comparison

How better-code-review-graph stacks up against direct competitors in each pillar:

Capability better-code-review-graph Greptile Sourcegraph (Cody / MCP) CodeGraph (colbymchenry)
Codebase knowledge graph Yes (Tree-sitter, 14 langs, SQLite) Yes (functions/classes/deps) Yes (precise code indexing) Yes (Tree-sitter, 20+ langs, SQLite)
Persistent incremental updates Yes (git-diff + file-hash re-parse) ? Yes (continuous indexing) Yes (OS file-watcher debounced)
Qualified call resolution (callers/callees) Yes (same-file bare-call resolution + fallback) ? Yes (go-to-def / find-references) Yes (callers / callees / impact)
Semantic search / embeddings Yes (fastretrieval local registry + cloud Jina/Gemini/OpenAI/Cohere) ? Yes (semantic + keyword + regex) No (FTS5 full-text only)
Token-optimized review context Yes (review tool, git-diff scoped) Yes (PR review comments) No (code-context assistant) No (context layer, not review)
Security scanning Yes (Semgrep p/auto + 3-rule overlay, SARIF) ? ? No
Self-hostable Yes (stdio default, machine-bound) Yes (Docker / K8s / air-gapped) Yes (self-hosted instance) Yes (100% local, no API keys)
Free / open source Yes (Apache-2.0) No (proprietary SaaS; free OSS tier) No (Enterprise license, source private) Yes (MIT)

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/crg
cd better-code-review-graph
uv sync --group dev
uv run pytest
uv run better-code-review-graph

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.

Mode Graph DB Cloud credentials Who can read your data?
stdio (default) <repo>/.better-code-review-graph/graph.db (git-ignored) ~/.better-code-review-graph-mcp/config.json (AES-GCM, machine-bound key) Only your OS user
HTTP self-host (multi-user) Per-user ~/.crg/subs/<sub>/graph.db Per-user ~/.crg/subs/<sub>/config.json Only the authenticated user

Migration & changelog

Graph, security scan cache, and suppression state now use the package-owned.better-code-review-graph/ directory. Run graph(action="build", full_rebuild=true)once after upgrading, followed by graph(action="embed") if semantic search isneeded. The ambiguous old .code-review-graph/ and .code-review-graph.db pathsand their SQLite sidecars are left untouched: they may belong to the separateupstream package. Review and reapply any desired suppression rules explicitly.

The v2.0 release added temporal columns (valid_from_sha / valid_to_shaon every node and edge) plus an opt-in security scanner. The schema migrationis auto-applied on first GraphStore open, and a backup of the pre-2.0 DB iswritten 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 atmcp.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.

MCP Server · Populars

MCP Server · New

    n24q02m

    Better Code Review Graph

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

    Community n24q02m
    Noveum

    Orbit

    Free, open source, realtime task manager. Issues, boards, sprints, projects and docs that sync instantly. Keyboard-first, self-hostable, with an MCP server for AI agents. No pricing, ever.

    Community Noveum
    feder-cr

    aihawk

    Anti detect browser and web browsing agent: an open-source MCP server for undetected browsing, AI web scraping and computer use agents. No captchas.

    Community feder-cr
    LeandroPG19

    MemoryIndustry

    Persistent memory MCP server for AI agents — Rust, 19 tools, knowledge graph, Hebbian learning, episodic memory, contradiction detection, prospective triggers, Bayesian calibration, zero-config Docker setup.

    Community LeandroPG19
    btsouth

    Toolport

    Local-first MCP gateway. One port for every tool and every AI client: lazy discovery (~90% token savings), tool integrity + quarantine, secrets in the OS keychain.

    Community btsouth