MCP Capabilities Reference

Documentation Resources

Browse these via MCP resource URIs. Each is a self-contained, agent-optimized guide. All resources work without an API key.

Resource URI	Description
waxell://docs/quickstart	5-minute setup: install, configure, instrument, verify
waxell://docs/sdk-reference	Full Python SDK API — every function with signature and example
waxell://docs/cli-reference	All wax CLI commands with flags and examples
waxell://docs/integrations	Per-provider guides: OpenAI, Anthropic, LangChain, LiteLLM, Groq
waxell://docs/controlplane	Controlplane UI navigation — every section and URL
waxell://docs/governance	Policy categories, enforcement, scoping, configuration
waxell://docs/cowork	Claude Cowork integration: hooks, guard, monitoring
waxell://docs/troubleshooting	Common issues and solutions

Live Platform Tools

All tools require a valid API key. Returns JSON data from your Waxell instance.

Setup & Account

waxell_check_connection() Verify your API key, check fleet status, and get guided next steps based on your current state. Always call this first.

waxell_get_config() Show current configuration (API key masked, URL, source).

waxell_setup_guide() Return the quickstart guide inline for agents that don't browse resources.

waxell_signup() Start the browser-based signup flow using device authorization. Returns a URL for the user to open. No password touches the conversation.

waxell_signup_status(session_id) Complete the signup flow and retrieve the API key. Call after the user finishes the browser form.

Fleet Monitoring

waxell_agent_fleet(hours=24) List all agents with health metrics, execution counts, and success rates.

waxell_agent_detail(agent_name, hours=24) Deep-dive on a specific agent: recent runs, error rate, model usage.

Runs & Executions

waxell_recent_runs(hours=24, agent_name="", status="") Summary of recent runs: total, by status, by agent, trend. Filter by agent or status (success, error, running).

waxell_run_detail(agent_name, status="error", hours=24) Investigate runs for a specific agent, typically errors.

Costs

waxell_cost_summary(hours=24, model="") Total cost, tokens, by-model breakdown, and trend.

waxell_model_usage(hours=24) Which models are being used, call counts, costs per model.

Errors

waxell_error_summary(hours=24, agent_name="") Error rate, errors by agent, and recent error details.

Governance

waxell_policy_summary(hours=24) Policy pass rate, violations by policy, recent violations.

waxell_policy_list() All active policies with configuration.

waxell_recommendations() AI-generated policy recommendations based on observed agent behavior.