This MCP server exposes a single tool, get_status, with minimal definition quality. The tool has a generic empty schema (no parameters), a very brief description (71 chars), and no output schema documentation. The tool merely wraps AgentReach's internal doctor_report() call. Error handling is present but basic (generic TextContent wrapping). No security considerations are evident (though the tool is read-only). The server demonstrates understanding of MCP fundamentals but falls short of production quality across multiple dimensions. The tool is explicitly registered (not inferred), so it is not artificially capped.

• Expand tool description to 120-200 characters. Include: what status information is provided (installed channels, activation state, version info), when an LLM should call this (at the start of a session? to verify channel availability?), and what the response structure contains (e.g., 'Returns a dict with keys: channels (list of dicts with name, installed, active), backend_status (dict with service health), version').
• Document the output schema explicitly. Create a response schema comment or docstring that lists all top-level keys, their types, and meanings. Example: 'Returns {"channels": [{"name": str, "installed": bool, "active": bool, "version": str?}], "backends": {...}, "errors": [...]}'.
• Rename tool from 'get_status' to 'get_agent_reach_status' or 'get_channel_installation_status' to disambiguate from system/API status checks.
• Implement error classification. Catch specific exception types and return structured errors with recovery hints. Example: If a backend is unreachable, return 'Backend unavailable: {backend_name}. Try again in 30s or check network connectivity.' instead of a generic error.
• Add parameter validation. Although no parameters are expected, validate that the call passes no arguments, or explicitly document that any arguments are ignored. This prevents confusion if a user mistakenly passes a parameter.
• Return a JSON object with documented fields (not raw doctor_report()). Wrap the response in a known schema so LLMs can reliably extract channel names, versions, and health status without parsing free-form text.