Code Auditor MCP

Code Auditor

Architectural invariants enforced inside your AI agent's edit loop. When the agent writes code that breaks a project rule, Code Auditor catches it and blocks the edit. The agent sees the rule's message and fixes itself.

Install

npm install -g code-auditor-mcp

code-audit install --agent all

Two commands to install everywhere. code-audit install --agent all copies the skill to every AI coding tool on your machine. Use --agent for specific tools.

What you get per tool: the skill (SKILL.md), MCP server access, and hook wiring where the tool supports it (blocking on Claude Code and Codex, advisory on Cursor).

code-audit install --list   # see the support matrix

Claude Code users can also install via plugin:

claude plugin marketplace add BenAHammond/code-auditor-mcp

claude plugin install code-auditor

The hook auto-installs the auditor on first use via npx.

Requirements

• Node 18+ to run. Node 23.4+ gets the zero-native-install path: Code Auditor uses the built-in node:sqlite module, so nothing needs to compile or download a prebuilt binary on install.
• On older Node (18–23.3), Code Auditor falls back to better-sqlite3, an *optional* dependency whose install script must be approved once on npm 11.2+/12 (they block dependency install scripts by default): npm install-scripts approve better-sqlite3 && npm rebuild better-sqlite3 (with pnpm: pnpm approve-builds, then select better-sqlite3).

Configuration

Project-level settings live in .codeauditor.json (invariant rules, analyzer settings, and thresholds). Eleven environment variables additionally tune process-scoped behavior — worker pool size, daemon and job-queue timeouts, the index location, the SQLite backend, and the UI port.

When CODE_AUDITOR_DATA_DIR is set, the index is scoped per project ( /projects/ /index.db) so projects can't leak data into each other. When unset, the index lives in a user-level OS cache ( /code-auditor/projects/ /index.db) so it never lands inside the audited repo.

Prompt examples

"Index the codebase and run a full audit, then walk the violations file-by-file with `code-audit next-file`."

"Create a `.codeauditor.json` that bans lodash imports and prevents `src/languages/` from importing anything in `src/analyzers/`."

"Run a full audit, fix the highest-priority file, and repeat `code-audit next-file` until the tree is clean."

"Sync the code index and audit only what changed vs main."

"Add an ast-pattern rule that blocks `new Function(...)`."

"Add a naming rule requiring hooks in `src/hooks/` to start with `use`."

"Add a call-constraint so `chargeCustomer()` in `src/services/payment.ts` can only be called from `src/api/`."

Rule kinds

Seven kinds. The agent writes them to .codeauditor.json. Bad configs fail the audit, not silently.

Works with your agent

One skill, one CLI, one MCP server. Every agent gets the same audit engine — the hook contract is the only difference.

MCP config generation covers a wider set than skill install. The MCP server's generate tool writes a client config file for any of claude, codex, cursor, gemini, copilot, continue, awsq (AWS Q Developer), codeium (Codeium/Windsurf), vscode, cline, and zcode. Four of those — Continue, AWS Q Developer, Codeium/Windsurf, and Cline — are MCP-only: they have no file-based skill or hook path, so they connect through the generate tool rather than code-audit install.

Hook behavior: Blocking means the diff-scoped changed gate is tripped — an invariant rule that declares gating: true (a binary, per-rule flag, independent of severity) blocks the edit from landing (the agent sees the violation and fixes inline). Advisory means violations are reported through the strongest available feedback channel but the edit has already occurred. Cursor's afterFileEdit hook is fire-and-forget with no output consumption. MCP is available everywhere for shell-less use.

Findings: Deterministic vs Advisory

Code Auditor's built-in rules fall into two categories:

Deterministic rules ship at critical or severe. Advisory rules ship at severe or high. Rules proven near-zero precision on a real corpus are disabled by default (off) — users opt in when the rule matches their domain.

Recalibration

Built-in severity defaults are recalibrated from real-corpus triage. The current defaults reflect measurement on three corpora: this tool's own codebase, Gin, and Excalidraw. Six data-access rules that produced near-zero precision across all three corpora are disabled by default.

Every disabled rule documents what corpus it *would* be useful on. Users can restore any rule via severityOverrides in .codeauditor.json:

{

"severityOverrides": { "sql-injection-risk": "critical", "missing-org-filter": "severe", "loop-query": "severe" } }

Severity overrides apply globally (before per-directory path profile caps). Setting a rule to "off" removes it from the output entirely.

SQL Injection Detection

The sql-injection-risk rule is disabled by default (off) after recalibration. On the self-audit corpus, it produced 0% precision — the rule misinterpreted TypeScript pattern-matching code (string constants like 'SELECT', 'FROM', 'WHERE' used for the tool's own SQL detection) as database queries. On the Gin and Excalidraw corpora, precision was also near zero.

When to re-enable it: your project's SQL is constructed via string concatenation or template literals in functions whose sole purpose is query assembly. The rule detects those patterns. For codebases using ORMs or parameterized queries exclusively, the rule produces noise.

To re-enable and block on SQL injection:

{

"severityOverrides": { "sql-injection-risk": "critical" } }

With sql-injection-risk: critical (and the rule marked gating), your agent's hook will block edits that introduce AST-level SQL injection patterns.

Dismissals

Every finding is a measurement, not a verdict — but measurements are occasionally wrong. When the agent hits a false positive (the rule is right in general, wrong for this specific code), it can dismiss *that one instance* rather than work around it:

code-audit dismiss <fingerprint> --reason "generated code, not hand-written"

The comes from the JSON report (every violation carries a fingerprint field). A written `--reason` is required, and the dismissal clears exactly one finding — rule + file + symbol — so the same rule still fires everywhere else. Dismissals live in a committed .codeauditor.dismissals.json, reviewable in a diff.

Anonymous dismissal feedback (opt-in)

The reason an agent gives for dismissing a finding is the most useful signal for improving the rules. Code Auditor can send dismissed findings to an anonymous feedback service that collects them.

It is off by default and turned on only by an explicit opt-in, via any of three methods (in precedence order):

1. per-invocation — code-audit dismiss --telemetry … sends just that one dismissal; --no-telemetry suppresses one.
2. environment — CODE_AUDITOR_TELEMETRY=1 (or 0) as a machine-level default for headless/CI runs.
3. persisted — code-audit telemetry status|enable|disable (or the telemetry MCP tool), which records the choice in your user config dir.

telemetry enable needs no arguments: it opts in against the built-in service endpoint (overridable for self-hosting). Opting in generates an anonymous install ID: a random value generated locally, never derived from your machine, user, or project, used only to group submissions by source.

What is sent — the tool version, the rule ID, the urgency level, the dismissal reason exactly as typed, a structural AST signature (grammar kinds only, never their contents), a coarse language hint, a timestamp, and the anonymous install ID. What is never sent — source code, identifiers, literals, file paths, or anything derived from your code or environment. Sending is best-effort: offline or an unreachable endpoint is silent and never blocks an edit or fails a gate.

Style Intelligence

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