This is a stub verification server, not a production MCP implementation. All three tools are explicitly defined with schemas and descriptions, but they are deliberately non-functional, they return setup guidance rather than real API results. Tool definitions meet minimum structural requirements but lack depth expected for production use. Naming is clear (docs, search, execute), descriptions are present but brief (27 - 67 chars), and input schemas are minimal but valid. Tool annotations are declared correctly. However, the stub nature means these tools cannot actually serve agents; they exist solely to advertise the published protocol version and tool list. This severely limits practical utility. For evaluation purposes, the definitions themselves are moderately well-formed, but the lack of functional implementations, absent output schemas, no error handling guidance, and minimal parameter descriptions place this squarely in the 'poor' range.

• Add detailed output schemas to all tools. Document the JSON structure returned on success (e.g., 'docs returns {"results": [{"title": string, "url": string, "snippet": string}], "totalCount": number}').
• Expand tool descriptions to 100 - 150 characters. Include context: 'Search Xquik documentation to find setup guides, API references, and examples. Call this first if unsure about available endpoints or authentication methods.'
• Add parameter descriptions with examples and constraints. For 'code' param: 'JavaScript async arrow function. Example: `async () => { const endpoints = await spec.endpoints(); return endpoints.filter(e => e.includes('search')); }`. Must return a Promise.'
• Implement actual tool handlers instead of returning setup guidance for all calls. The stub should at least validate inputs and return meaningful errors (e.g., 'docs: query is required and must be 1 - 500 characters').
• Add per-tool error guidance. Document expected failures: 'docs may return 404 if no matching documentation is found. Try a broader query or check https://docs.xquik.com.'
• Remove or constrain the 'code' parameter. Accepting arbitrary JavaScript is a security risk and requires LLMs to write code. Consider replacing with structured parameters (e.g., search_term, max_results, endpoint_type) to match the chat data model.
• Declare all tool annotations accurately. Currently all three tools declare annotations, ensure they reflect real behavior (e.g., 'execute' with destructiveHint=true and idempotentHint=false is correct, but verify 'search' truly has openWorldHint=false).

Inferred effective spec: <=2025-11-25.

• Relies on Sampling (deprecated) - integrate directly with the LLM provider API