codebase-intelligence MCP server
Commit 22. Okt. 2026Analysiert TypeScript-Codebases, um Architekturmetriken, Dependency-Impact-Analysen und Dead-Code-Erkennung für AI Agents und Entwickler bereitzustellen.
Auch bekannt als bntvllnt/codebase-intelligence
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Was ist codebase-intelligence MCP?
codebase-intelligence ist ein MCP server. Analysiert TypeScript-Codebases, um Architekturmetriken, Dependency-Impact-Analysen und Dead-Code-Erkennung für AI Agents und Entwickler bereitzustellen.
Zusammenfassung generiert aus dem README des Projekts
Über codebase-intelligence MCP server
codebase-intelligence ermöglicht es Entwicklern und AI Agents, TypeScript-Codebases zu analysieren, um Architekturmetriken, Dependency-Impact-Analysen und Dead-Code-Erkennung durchzuführen. Es fungiert primär als CLI-first Tool, das Projekte parst, um Dependency-Graphen zu erstellen und komplexe Qualitätsmetriken wie PageRank, Kopplung und zyklomatische Komplexität zu berechnen. Nutzer können es via npx ausführen oder global installieren, um tiefgehende Inspektionen ihrer Source-Verzeichnisse durchzuführen.
Obwohl die CLI die primäre Schnittstelle ist, enthält es eine optionale MCP Implementierung, die 25 Tools, 2 Prompts und 3 Resources für die Nutzung in Clients wie Claude oder Cursor bereitstellt. Der Server kann lokal über stdio eingerichtet werden. Er ist darauf ausgelegt, Teams dabei zu helfen, Hotspots zu identifizieren, doppelte Funktionsfamilien zu erkennen und Architektur-Grenzen mithilfe von Presets wie layered oder hexagonal durchzusetzen. Durch die Integration mit AI Agents via init Command wird sichergestellt, dass Modelle strukturierte Codebase-Intelligence abfragen, anstatt sich auf einfache Textsuche zu verlassen.
Was du damit machen kannst
- 1High-Risk Code Hotspots identifizierenRanke Dateien basierend auf spezifischen Metriken wie Komplexität, Churn oder Blast Radius, um Bereiche zu finden, die ein Refactoring benötigen.
- 2Ungenutzte Code-Exports erkennenFinde dead exports innerhalb eines TypeScript-Projekts, um die Codebase sicher aufzuräumen.
- 3Dependency-Impact analysierenBestimme den Blast Radius eines Symbols, um zu sehen, welche Dateien von einer Änderung betroffen sind.
- 4Architektur-Grenzen durchsetzenVerifiziere, dass Imports spezifischen Architekturmustern wie layered oder hexagonal Designs folgen.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
Automatisierte Checks
Geluften am 14. Nov. 2026Vollständiger Bericht →Noch nicht verifiziert. Ein Server benötigt einen Score von 80, keine kritischen Befunde und genug Daten für unsere Prüfung. Wie die Checks funktionieren · Was du für mehr Punkte verbessern kannst
- Source Repository verknüpft und erreichbarbntvllnt/codebase-intelligence is public and reachablegithub.com/bntvllnt/codebase-intelligence ↗Bestanden
- Paket nennt dieses Repository als QuelleNicht geprüft
- Build-Provenienz (Sigstore-Attestierung)Nicht geprüft
- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-10-22github.com/bntvllnt/codebase-intelligence ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNicht geprüft
- Keine kritischen Advisories im Paket oder seinen AbhängigkeitenNicht geprüft
- Keine versteckten Anweisungen an das Modell0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNicht geprüft
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehencodebase-intelligence
CLI-first codebase analysis for TypeScript projects.
Parse your codebase, build a dependency graph, compute architectural metrics, and query everything from your terminal/CI. MCP support is included as an optional secondary interface.
Quick Start
CLI (recommended)
npx codebase-intelligence overview ./src
Common workflows:
npx codebase-intelligence hotspots ./src --metric complexity --limit 10
npx codebase-intelligence opportunities ./src --limit 10
npx codebase-intelligence duplicates ./src --mode mild --min-tokens 30
npx codebase-intelligence impact ./src parseCodebase
npx codebase-intelligence dead-exports ./src --limit 20
npx codebase-intelligence changes ./src --json
npx codebase-intelligence boundaries ./src --preset layered --list --json
MCP (optional)
claude mcp add -s user -t stdio codebase-intelligence -- npx -y codebase-intelligence@latest .
Table of Contents
- Features
- Installation
- CLI Usage
- Agent Adoption
- MCP Integration (Secondary)
- Metrics
- Architecture
- Requirements
- Limitations
- Release
- Security
- Contributing
- License
Features
- 24 CLI commands for architecture analysis, dependency impact, duplicate families, focused map/context packs, content drift, health scoring, boundary enforcement, Highways convergence, improvement opportunities, dead code detection, search, CI rules, and agent setup
- Machine-readable JSON output (
--json) for automation and CI pipelines - Auto-cached index in
.codebase-intelligence/for fast repeat queries - Cache migration facts in JSON (
cacheDir,legacyCacheDir,migrated,gitignoreUpdated,warnings[]) - Quality metrics — PageRank, betweenness, coupling, cohesion, tension, churn, cyclomatic/cognitive complexity, blast radius, dead exports, test coverage, escape velocity, risk, maintainability, and CRAP score
- Symbol-level analysis — callers/callees, symbol importance, impact blast radius
- BM25 search — ranked keyword search across files, symbols, and type/shape facts
- Process tracing — detect entry points and execution flows through the call graph
- Codebase maps + context packs — focused file/symbol/test graph with deterministic evidence IDs and token-bounded context for agents
- Content drift — report-only detection for file/name/scope/side-effect/shape/test placement mismatch with stable evidence
- Health score — CI-gateable composite score with per-file maintainability, CRAP, coverage source, and risk hotspots
- Highways analysis — find repeated routes that bypass canonical dataflow paths and synthesize safe proposed highways
- Community detection — Louvain clustering for natural file groupings
- Agent adoption —
initwrites per-agent instruction files + installs a skill so AI agents query CI before grep/read - MCP parity (secondary) — same analysis and rules gate available as 25 MCP tools, 2 prompts, and 3 resources
Installation
Run directly with npx (no install):
npx codebase-intelligence overview ./src
Or install globally:
npm install -g codebase-intelligence
codebase-intelligence overview ./src
CLI Usage
codebase-intelligence <command> <path> [options]
Commands
| Command | What it does |
|---|---|
overview |
High-level codebase snapshot |
hotspots |
Rank files by metric (coupling, churn, complexity, cognitive complexity, blast radius, coverage, risk, etc.) |
file |
Full context for one file |
search |
BM25 keyword and shape search |
changes |
Git diff analysis with risk metrics |
dependents |
File-level blast radius |
modules |
Module architecture + cross-dependencies |
forces |
Cohesion/tension/escape-velocity analysis |
dead-exports |
Unused export detection |
opportunities |
Ranked code-quality and refactoring opportunities |
duplicates |
Duplicate function families (strict, mild, weak) |
groups |
Top-level directory groups + aggregate metrics |
symbol |
Callers/callees and symbol metrics |
impact |
Symbol-level blast radius |
rename |
Reference discovery for rename planning |
processes |
Entry-point execution flow tracing |
map |
Focused codebase graph + token-bounded context pack |
drift |
Report-only content drift findings with evidence and recommendations |
health |
CI-gateable health score with maintainability, CRAP, coverage, and risk hotspots |
boundaries |
Architecture boundary zones, allow/forbid import rules, and violation evidence |
highways |
Repeated route convergence, canonical path opportunities, and synthesis proposals |
clusters |
Community-detected file clusters |
owners |
Ownership, bus-factor, and risk grouping |
architecture |
Evidence-backed extraction/seam/locality recommendations |
workspaces |
Package workspace scope and changed-workspace detection |
lsp |
Advisory editor diagnostics snapshot or minimal LSP server |
watch |
Local watch readiness and debounced analysis events |
check |
Rules-engine gate for CI, including opt-in dead-code and dependency gates |
ci |
One PR quality gate around check, changes, health, formats, baselines, and history |
doctor |
Read-only setup auditor for local, CI, MCP, and agent workflows |
explain |
Explain one analyzer rule and next action |
migrate-config |
Dry-run config migration to codebase-intelligence.json |
hooks |
Plan or install local hooks that run the same CI gate |
history |
Read local finding history from .codebase-intelligence/ |
init |
Set up AI agents to use CI — writes per-agent instruction files (skill opt-in via --skill) |
Useful flags
| Flag | Description |
|---|---|
--json |
Stable JSON output |
--force |
Rebuild index even if cache is valid |
--limit <n> |
Limit results on supported commands |
--metric <m> |
Select ranking metric for hotspots |
--scope <s> |
Select git diff scope for changes; directory/module scope for map and drift |
--mode <m> |
Select clone mode for duplicates: strict, mild, weak |
--min-tokens <n> |
Minimum duplicate token size for duplicates |
--skip-local |
Ignore duplicate families confined to one file |
--trace <id> |
Return token evidence for one duplicate family |
--focus <name> |
Focus map or drift on one symbol, file, or scope |
--context-budget <n> |
Bound map context pack size |
--min-score <n> |
Minimum drift score for drift findings; minimum health score before health exits 1 |
--score |
Print compact health score text |
--preset <name> |
Run boundaries with bulletproof, layered, hexagonal, or feature-sliced |
--list |
List resolved boundaries zones and rules |
--format <fmt> |
Export map as markdown, json, dot, or graphml; export check/ci as text, json, sarif, markdown, annotations, pr-comment-github, pr-comment-gitlab, badge, codeclimate, or compact |
--operation <verb> |
Focus highways on one operation verb |
--shape <name> |
Focus highways on one type/DTO shape |
--production |
Exclude test/dev files from production-risk check/ci output |
--changed-since <ref> |
Line-level check/ci filtering from a git diff |
--diff-file <path> |
Line-level check/ci filtering from a unified diff file |
The scanner always excludes common generated and agent-workspace directories such as .codebase-intelligence/, legacy .code-visualizer/, .next/, dist/, coverage/, .worktrees/, and .claude/worktrees/.
Analysis commands with --json and init --json include a top-level cache object with the canonical cache path, legacy cache path, migration status, .gitignore update status, and non-fatal cache warnings.
For full command details, see docs/cli-reference.md.
Agent Adoption
codebase-intelligence has the data — but AI agents only benefit if they actually
query it instead of defaulting to grep/read. init closes that gap.
codebase-intelligence init # interactive picker (TTY)
codebase-intelligence init --agents claude,cursor
codebase-intelligence init --all --skill # every agent + global skill
codebase-intelligence init --yes # non-interactive defaults
Nothing is written unless you choose it. On a terminal, init shows an interactive
picker (AGENTS.md + CLAUDE.md preselected); non-interactively it defaults to those
two. The global skill is opt-in (--skill). It writes an idempotent, marked
instruction block ("query CI before grep/read") into each selected agent's native file:
| Layer | Target | Default |
|---|---|---|
| Repo instructions | AGENTS.md, CLAUDE.md |
selected |
| Repo instructions | .cursor/rules/*.mdc, .github/copilot-instructions.md, GEMINI.md, CONVENTIONS.md (Aider) |
opt-in |
| Portable skill | ~/.claude/skills/codebase-intelligence/SKILL.md |
opt-in (--skill) |
Writes are idempotent — only content between the
<!-- codebase-intelligence:start --> / :end markers is ever touched, so re-running
is safe and your own edits are preserved.
Install the skill directly
The skill is also published to the skills.sh registry:
ags install codebase-intelligence
# or
npx skills add github.com/bntvllnt/codebase-intelligence
MCP Integration (Secondary)
Running without a subcommand starts the MCP stdio server (backward compatible):
npx codebase-intelligence ./src
Claude Code (manual)
Add to .mcp.json:
{
"mcpServers": {
"codebase-intelligence": {
"type": "stdio",
"command": "npx",
"args": ["-y", "codebase-intelligence@latest", "./src"],
"env": {}
}
}
}
Cursor / VS Code
Add to .cursor/mcp.json or .vscode/mcp.json:
{
"servers": {
"codebase-intelligence": {
"command": "npx",
"args": ["-y", "codebase-intelligence@latest", "./src"]
}
}
}
For MCP tool details, see docs/mcp-tools.md.
Metrics
| Metric | What it reveals |
|---|---|
| PageRank | Most-referenced files (importance) |
| Betweenness | Bridge files between disconnected modules |
| Coupling | How tangled a file is (fan-out / total connections) |
| Cohesion | Does a module belong together? (internal / total deps) |
| Tension | Is a file torn between modules? (entropy of cross-module pulls) |
| Escape Velocity | Should this module be its own package? |
| Churn | Git commit frequency |
| Complexity | Average cyclomatic and cognitive complexity of exports/symbols |
| Blast Radius | Transitive dependents affected by a change |
| Dead Exports | Unused exports (safe to remove) |
| Test Coverage | Whether a test file exists for each source file |
| Risk Score | Composite file risk from complexity, churn, coupling, size, blast radius, and test reachability |
| Maintainability Index | Health-derived 0-100 per-file maintainability score |
| CRAP Score | Complexity x uncovered-code risk, using Istanbul coverage when present or static test reachability otherwise |
Architecture
codebase-intelligence <command> <path>
|
v
+---------+ +---------+ +----------+
| Parser | --> | Graph | --> | Analyzer |
| TS AST | | grapho- | | metrics |
| | | logy | | |
+---------+ +---------+ +----------+
|
+--> CLI output (default)
+--> MCP stdio (optional mode)
- Parser — extracts files, functions, and imports via TypeScript Compiler API.
- Graph — builds dependency/call graphs with graphology.
- Analyzer — computes file/module/symbol metrics.
- Interfaces — CLI is primary; MCP is available for agent integrations.
Requirements
- Node.js >= 18
- TypeScript codebase (
.ts/.tsxfiles)
Limitations
- TypeScript-focused analysis
- Static analysis only (no runtime tracing)
- Call graph confidence varies by symbol resolution quality
Release
Publishing is automated through GitHub Actions. See CHANGELOG.md for release notes.
Normal CI (before release)
CIworkflow runs on every PR and push tomain:- lint → typecheck → build → test
Canary publish
- Pushes to
maintrigger a canary publish. - The package is published to npm with the
canarytag. - Canary versions are derived from the current package version plus the short commit SHA.
Create a release
- Bump
package.jsonversion in a normal PR. - Merge that PR to
main. - Run the
Publishworkflow manually from GitHub Actions. - The workflow will:
- verify the tag does not already exist
- create and push
vX.Y.Z - publish to npm with provenance via OIDC
- create a GitHub Release with generated notes
No PAT is required for npm publish. The workflow uses GitHub repository permissions for tagging and OIDC for npm publishing.
Security
Please do not report security vulnerabilities in public issues.
- Read
SECURITY.mdfor supported versions and disclosure guidance. - Use GitHub Security Advisories or private maintainer contact for sensitive reports.
Contributing
Contributions are welcome.
Start here:
CONTRIBUTING.md— setup, workflow, testing, and PR expectationsCODE_OF_CONDUCT.md— community standardsSECURITY.md— vulnerability reporting
Quick setup:
git clone https://github.com/bntvllnt/codebase-intelligence.git
cd codebase-intelligence
pnpm install
pnpm dev # tsx watch mode
pnpm test # vitest
pnpm lint # eslint
pnpm typecheck # tsc --noEmit
pnpm build # production build
pnpm verify:cli-real # default real-repo CLI matrix
pnpm verify:cli-real:heavy # large /home/ubuntu repo matrix
License
codebase-intelligence MCP Fragen
Wie kann ich codebase-intelligence mit Claude nutzen?
Du kannst es als MCP server hinzufügen mit dem Befehl: claude mcp add -s user -t stdio codebase-intelligence -- npx -y codebase-intelligence@latest .
Unterstützt es CI/CD-Pipelines?
Ja, es liefert maschinenlesbare JSON-Outputs und spezifische Commands wie check und ci, die als Quality Gates in CI-Umgebungen dienen können.
Kann es mir helfen, ungenutzten Code zu finden?
Ja, es enthält einen dead-exports Command, der speziell dafür entwickelt wurde, ungenutzte Exports zu finden.
Wie hilft es AI Agents dabei, besser mit meinem Code zu arbeiten?
Der init Command schreibt Instruktionsdateien für Agents wie Claude oder Cursor, damit diese lernen, das Tool für Kontext abzufragen, anstatt sich auf einfache grep/read-Befehle zu verlassen.