This MCP server has a single tool (get_suggestions) with moderate definition quality issues. The tool has a valid name and description, but critical gaps exist in schema completeness, parameter documentation, output schema specification, and error handling. The implementation is a mock/demo service without proper MCP integration, making this unsuitable for production use.

• Document the full output schema as JSON Schema. Specify that suggestions is an array of strings, query_expansion is an object with original_query (string) and expanded_terms (array of strings). Example: {'suggestions': ['zenith speaker pro', 'zenith wireless headphones'], 'query_expansion': {'original_query': 'zeni', 'expanded_terms': ['zeni', 'zenith']}}
• Expand the prefix parameter description to: 'The search query prefix to match against indexed terms (case-insensitive). Accepts 1-100 characters, including spaces for multi-word queries. Examples: "zeni", "wireless speaker". Special characters are stripped.'
• Add explicit error handling that returns structured errors. E.g., if prefix is empty, return {'error': 'prefix_required', 'message': 'Prefix must be 1-100 characters'}. If limit < 1 or > 100, return {'error': 'invalid_limit', 'message': 'Limit must be 1-100'}.
• Implement and document pagination: add an optional 'offset' parameter (default 0) and return {'suggestions': [...], 'total_count': N, 'offset': 0, 'limit': 5, 'query_expansion': {...}}. This allows agents to fetch all results if needed.
• Integrate with MCP protocol: wrap the SearchSuggestClient in an MCP server (STDIO or HTTP transport), register get_suggestions as a tool with full schema metadata, and implement the protocol handshake.
• Replace hardcoded mock data with a real search backend (e.g., database query, Elasticsearch, or API call). Document how to configure the backend via environment variables or config.
• Add rate limiting: document that the tool is limited to 100 calls per minute per agent. Return a 429 error with Retry-After guidance if exceeded.