Policy-as-code guardrails for AI coding agents, validated via OPA, Conftest, Checkov & Semgrep.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Policy-as-code guardrails for AI-generated code. An MCP server that serves engineering constraints to coding agents (Claude Code, Cursor, Codex) at generation time and validates artifacts with OPA, Conftest, Checkov, and Semgrep.
A single, queryable source of engineering constraints (infrastructure, organizational, architectural) that coding agents (Claude Code, Cursor, Codex, β¦) consult at code-generation time, exposed over an MCP server. It does not enforce constraints itself β it provides guidance to agents and delegates deterministic validation to existing enforcement engines (OPA, Conftest, Checkov, Semgrep).
Constraints are authored in source repos, aggregated into an immutable, versioned bundle, and served over MCP so an agent can:
describe_scope β discover the valid selector vocabulary,get_constraints β fetch the rules relevant to what it's building, andvalidate β check a candidate artifact against the bound enforcement engines.Authoritative requirements:
constraint-registry-v0-spec.md. Requirement β component β test mapping:TRACEABILITY.md.
adapters/sarif/), so adding a new SARIF engine is mostly
wiring. Adding an engine = one adapter + one config line (see
Adding an enforcement engine).describe_scope, get_constraints, validate)
over stdio or a shared HTTP endpoint. get_constraints fails open
so an agent is never blocked.| Tool | Required? | Notes |
|---|---|---|
| Python β₯ 3.11 | yes | the package targets 3.11+ |
| uv | yes | manages the venv and runs entry points |
OPA (opa) | for Rego validate / fixture cross-checks | the reference enforcement engine |
Conftest (conftest) | optional | second Rego engine; its checks SKIP if absent |
Checkov (checkov) | optional | IaC scanning engine; its checks SKIP if absent |
Semgrep (semgrep) | bundled | source-code engine; installed automatically by uv sync |
Install the external engines on macOS:
Each engine is optional and independent: any test or harness check whose
engine binary is not on PATH is skipped, not failed. The registry and the
get_constraints/describe_scope guidance work without any engine at all β an
engine is only needed to run validate and the fixture cross-checks for
constraints bound to it.
The harness emits machine-readable JSON and exits non-zero on any failure. A green run looks like:
(skip is used only when an optional engine like conftest is not installed.)
Two transports β pick based on how you want tools to connect.
Flags: --transport {stdio,http,sse}, --http (shorthand), --host
(default 127.0.0.1), --port (default 8765), --config
(or $CREGISTRY_CONFIG), --reload-interval SECONDS (0 = off).
Manage the shared HTTP server:
Full operational guide (stop/restart, macOS launchd auto-start, the
repo-sync/decoupling pattern): docs/RUNNING.md.
Tool input/output contracts: docs/MCP_CONTRACT.md.
The server exposes three tools: describe_scope, get_constraints, validate.
~/.cursor/mcp.json)Configure an MCP server with command: uv, args: ["run","--directory","/abs/path/to/repo","cregistry-mcp"].
Agents auto-discover the tools, but to get them to consult the registry before
generating code, add an instruction to your project (or ~/.claude/CLAUDE.md):
Before writing AWS/infra code, call the constraint-registry MCP:
describe_scopeto learn valid selector values, thenget_constraintswith the right scope, and comply with everyhardconstraint as a non-negotiable downstream gate. Optionallyvalidatethe result.
A source is a directory with constraints/*.yaml (one constraint per file)
and, optionally, policies/ (engine policies) and fixtures/ (sample artifacts).
Register sources and engines in registry.config.yaml:
A constraint (see sources/platform-security/constraints/aws-s3-no-public-access.yaml):
Scoping notes (matters when agents query):
resource_types use the target tooling's identifiers (Terraform: aws_s3_bucket).
Call describe_scope to discover the exact vocabulary present.uv run cregistry-harness to validate schema, precedence,
and fixtures.Run the server with --reload-interval N and it re-imports from disk every N
seconds, publishing a new immutable bundle when content changes:
git pull or CI publish). Code/dependency changes still need a restart.uv run cregistry-harness runs end-to-end against the bundled, self-contained
sample sources and proves: schema conformance, deterministic import, malformed-
constraint isolation, namespacing & precedence, versioning & deprecation, engine-
interface conformance (incl. a reusable suite any adapter can be run against),
fixture cross-checks / broken-binding detection, the MCP contract / scoping /
fail-open, and hot-reload behavior. It prints structured JSON and returns a
non-zero exit on any failure β suitable for CI.
Implement the EngineAdapter interface in a new module under
src/cregistry/engine/adapters/, add one line under engines: in
registry.config.yaml, and validate it against the existing conformance suite β
no changes to the schema, importer, MCP server, or harness. Full walkthrough:
docs/ADDING_AN_ENGINE.md.
Run the adapter test suite directly with uv run pytest.
Contributions are very welcome β bug reports, new engine adapters, constraint sources, and docs. Adding an engine is intentionally small: one adapter module plus one config line, with no changes to the schema, importer, MCP server, or harness.
Before opening a PR, make sure uv run pytest and uv run cregistry-harness are
green; CI runs both on every pull request.
Licensed under the Apache License 2.0. See NOTICE for attribution and the licenses of the external engines this project integrates with.
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