This MCP server exposes only 2 tools with minimal parameter complexity. Both tools have descriptions (good), but lack input schemas entirely, a critical failure. Tool names follow verb_noun convention (list_, get_), which is correct. However, the descriptions are terse (under 100 chars each) and lack actionable context for LLM selection. No output schemas are documented. The server is read-only (low risk), but the absence of formal schemas and sparse descriptions make it unsuitable for production agent integration. The tools appear to be discovery/guidance tools for the SDK itself, not operational tools, which limits their utility.

• Add explicit JSON Schema input definitions for both tools. Even if inputs are empty, declare `"type": "object", "properties": {}, "required": []` to signal schema completeness.
• Document output schemas. For list_adapters, specify: `{"type": "object", "properties": {"adapters": {"type": "array", "items": {"type": "object", "properties": {"name": {"type": "string"}, "status": {"enum": ["available", "planned"]}}}}}}`. For get_room_definition_guide, document the structure of the returned contract and example.
• Expand tool descriptions to 150 - 250 characters. Include: what the tool returns, when to call it (e.g., 'Call this first to understand available backend adapters before choosing one'), and what the agent should do with the result.
• Add optional parameters to make tools more useful: e.g., list_adapters could accept a `filter_by_status` enum (available|planned|all) to reduce response size and guide agent filtering.
• Consider adding a third tool, e.g., `validate_room_definition`, that accepts a RoomDefinition JSON and returns validation errors. This would shift the server from pure reference to operational guidance.