ActTrace

Classify AI systems under the EU AI Act and generate Article 50 transparency notices.

AI & MLPythonv0.1.0

ActTrace

A developer-facing EU AI Act compliance API for non-financial SaaS and technology companies. ActTrace gives an engineering team three things, self-serve, over an API or via MCP:

  1. A deterministic risk classification of an AI feature under the EU AI Act.
  2. A ready-to-ship Article 50 transparency notice.
  3. A free diagnostic as the public entry point.

Not legal advice. ActTrace provides operational compliance workflow support and documentation drafts. It does not provide legal advice, does not certify compliance, and does not replace review by qualified counsel. Every response carries this disclaimer.

ActTrace is scoped for non-financial companies. Financial-services use cases (banking, trading, portfolio/investment advice, credit scoring, …) are deliberately classified out_of_scope_financial_services.

Install — Claude Code plugin / MCP server

ActTrace ships as a Claude Code plugin: an acttrace skill plus a local MCP server. The MCP server runs via uvx — a deterministic rules engine, offline, no API key.

/plugin marketplace add goww7/acttrace
/plugin install acttrace@acttrace

Then ask Claude "Is my chatbot EU AI Act compliant?" or "Write an Article 50 notice for our support assistant." The MCP server also runs standalone with any MCP client: uvx acttrace-mcp.

Quickstart

python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
.venv/bin/uvicorn acttrace.app:app --reload --port 8080
# 1. Free diagnostic — no key needed
curl -s localhost:8080/api/acttrace/diagnostics/free -H 'content-type: application/json' -d '{
  "feature_name": "AI reply assistant",
  "description": "Drafts suggested customer support replies for agents.",
  "user_facing": true, "model_provider": "OpenAI", "use_case": "support_assist"
}'

# 2. Mint an API key
KEY=$(curl -s -XPOST localhost:8080/api/keys/generate | python3 -c 'import sys,json;print(json.load(sys.stdin)["api_key"])')

# 3. Classify (15 tokens)
curl -s localhost:8080/api/acttrace/classify -H "X-API-Key: $KEY" -H 'content-type: application/json' -d '{
  "feature_name": "AI reply assistant",
  "description": "Drafts customer support replies shown to agents.",
  "use_case": "support_assist", "user_facing": true, "model_provider": "OpenAI"
}'

# 4. Generate an Article 50 notice (10 tokens)
curl -s localhost:8080/api/acttrace/notices -H "X-API-Key: $KEY" -H 'content-type: application/json' -d '{
  "ai_system_name": "Support Copilot", "notice_type": "chatbot", "tone": "plain"
}'

Endpoints

Method & pathAuthTokensPurpose
POST /api/acttrace/diagnostics/freenone0Public risk diagnostic
POST /api/acttrace/classifykey15Documented risk classification
POST /api/acttrace/noticeskey10Article 50 transparency notice
POST /api/keys/generatenone0Issue a free-plan key
GET /api/healthnone0Liveness

Auth is X-API-Key. Responses carry X-Request-ID, X-Plan, X-Tokens-Charged, X-Tokens-Remaining, X-RateLimit-*. Errors are structured {"code","message","detail"} (401/403/429).

MCP

python -m acttrace.mcp_server --sse --port 8002 exposes two tools — acttrace_classify and acttrace_generate_transparency_notice — authenticated with the same X-API-Key. A Claude Code skill is in skill/acttrace/.

Tests

.venv/bin/python -m pytest -q

54 tests: classification engine (7 acceptance fixtures), conflict guard, notice generator, and HTTP API contract.

Deploy

docker-compose.yml builds a standalone two-container stack (API + MCP) on ports 8080 / 8002 with its own volume — isolated from FinanceData2. To go live, append caddy-acttrace.snippet to the shared Caddyfile (replace the placeholder domain). See BLUEPRINT.md for the full build contract.

Layout

acttrace/
  app.py config.py dependencies.py
  middleware/   api_key_auth.py
  routers/      acttrace.py  keys.py
  services/     acttrace_service.py  acttrace_classification_service.py
                acttrace_notice_service.py  acttrace_constants.py
                api_key_service.py
  repositories/ acttrace_repository.py  api_key_repository.py
  schemas/      acttrace.py
  mcp_server/   server.py  __main__.py  context.py  tools/acttrace.py
skill/acttrace/ SKILL.md  README.md
tests/

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx acttrace-mcp

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-goww7-acttrace": {
      "command": "uvx",
      "args": [
        "acttrace-mcp"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

acttrace-mcppypi

Compatible MCP Clients

ActTrace works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More