Server has 7 well-named tools with complete input schemas and descriptions. All tools follow verb_noun naming (search_apis, get_categories, probe_api, etc.). Schemas are properly typed with enums and constraints. However, output schemas are not documented, LLMs cannot predict response structure for downstream chaining. Error handling is basic (try/catch returns JSON error). No tool annotations (readOnlyHint, idempotentHint). Parameter descriptions are adequate but lack dependency hints and format constraints. Missing documentation of pagination behavior and result limits in responses.

• Document output schemas for all tools. E.g., search_apis should declare: 'Returns {apis: [{name, description, category, auth, https, url}], total, limit}'. This enables LLMs to chain tools (extract API name → call get_api_detail).
• Add tool annotations to all tools: set readOnlyHint=true for all 7 tools. This signals to agents that these tools are safe to call without confirmation.
• Remove apiKey parameters from probe_api and generate_snippet. Instead, accept an optional 'api_key_env_var' parameter (e.g., 'WEATHER_API_KEY') and read the secret from the server environment. Document: 'Pass the environment variable name; the server will inject the actual key.'
• Enhance error messages with recovery guidance. E.g., if get_api_detail('UnknownAPI') fails, return: 'API "UnknownAPI" not found. Try search_apis(query="unknown") to find similar APIs.' This guides the agent to self-correct.
• Add pagination documentation to search_apis and find_no_auth_apis. Clarify: 'Results are limited to 20 per call. Use limit parameter to adjust. No cursor/offset pagination available, refine query to narrow results.' This prevents agents from expecting pagination they cannot use.