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acdl/mcp/atelier/README.md
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Jon Chery 0d2cbdb423 feat(P1): remove gitea/gitlab from synced files + simplify docs (REQ-230,231,232)
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Drop .gitea byte-identity test assertions (keep GitHub-side + contract conformance).
Add test_no_forge_mentions.py guard test (REQ-230).
Delete completed migration docs (NOVA_MIGRATION.md, NOVA_AWS_MIGRATION.md).
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milestone headers, .ciagent/PROJECT.md citations).
Trim README.md (reusable deploy section, local key rotation paragraph).
Fix version-tag drift (@v1.13→@v1.19, acdl/→nova/).

---ci---
project: acdl
phase: 1
milestone: v1.20
status: execute
requirements: [REQ-230, REQ-231, REQ-232]
---/ci---
2026-08-07 18:20:29 +00:00

3.6 KiB

Nova Atelier MCP Server

exposes Atelier engineering principles to the citizen developer's AI agent. Plugin-registry architecture; stdio transport; vendored Atelier for audit reproducibility.

What This Is

The server exposes 4 tools that let a citizen developer's AI coding agent look up production-grade engineering principles and validate code against them — agentic validation that goes beyond deterministic scanners (Wiz, Checkmarx, Mend) by catching correctness, clarity, simplicity, and observability gaps.

Tools

Tool Description
atelier.lookup_principle(domain, principle_id) Look up a principle by domain + P-rule ID (e.g., security, P4). Returns the principle text + the core C-rule it derives from.
atelier.list_domains() List the 19 Atelier domains with P-rule counts + Nova-relevance.
atelier.matrix_lookup(domain) Look up the domain→core principle mapping for a given domain.
atelier.validate_against_principles(snippet, domains?) Validate a code/diff snippet against the Atelier agent-checklist. Returns pass/fail per check item with the principle citation.

Architecture — Plugin Registry

mcp/atelier/
├── server.py              # entrypoint: loads plugins, starts server
├── plugins/
│   ├── __init__.py
│   ├── principles.py       # lookup_principle, list_domains, matrix_lookup
│   └── validation.py       # validate_against_principles
├── vendor/                 # pinned Atelier snapshot
│   ├── VERSION.md           # pinned tag + upgrade instructions
│   ├── core/first-principles.md
│   ├── domains/security/first-principles.md
│   ├── review/agent-checklist.md
│   └── matrix/principles-matrix.md
└── README.md               # this file

Each plugin module exposes register(mcp) -> None and calls @mcp.tool() for its tools. server.py scans plugins/ and calls register on each. Future capabilities drop in as a new plugin file — no server.py edits.

Running

With the MCP Python SDK installed

pip install "mcp[cli]"
python3 -m mcp.atelier.server

The server runs over stdio. An MCP client (e.g., the citizen developer's AI coding agent) spawns it as a subprocess and calls tools via JSON-RPC.

Without the SDK (fallback / test mode)

The server degrades to a plain-Python tool registry. Tools are callable directly — this is how tests run without the SDK installed:

from mcp.atelier.server import NovaAtelierServer
s = NovaAtelierServer()
s.load_plugins()
result = s.call_tool("atelier_lookup_principle", {"domain": "security", "principle_id": "P4"})

Vendoring

Atelier is vendored under vendor/ at a pinned tag (v0.3.6, see vendor/VERSION.md). An agentic validation result is only reproducible if the principles that produced it are pinned. Live-fetch breaks replayability (Atelier main drifts). To upgrade:

bash scripts/update_atelier_vendor.sh <new-tag>

Extensibility

To add a new tool (e.g., a cost-estimation tool, a policy-as-code evaluator): create plugins/<name>.py, expose register(mcp), and call @mcp.tool() on your function. The server picks it up automatically. No server.py edit. This is the extensibility insurance for future capabilities.

Transport

  • Now: stdio (local agent consumption — the citizen developer's AI agent spawns the server as a subprocess).
  • Future: Streamable HTTP (the MCP SDK supports it on the same MCPServer object; adding it is a transport-only change in server.py, not a rewrite).