This RAG MCP server has significant definition quality gaps. While tool schemas are present with basic type information, descriptions are often translated from Chinese and lack actionable guidance for LLM selection. Most critically, output schemas are entirely undocumented, the server provides no specification of what fields agents should expect from tool responses. No parameter constraints (enums, ranges) are declared. Error handling lacks recovery guidance. The tool composition shows moderate coherence but overlapping concerns (build_knowledge_base, add_documents, and process_documents all manipulate the knowledge base with unclear responsibilities). No permission gates, audit trails, or security hardening visible despite destructive operations (clear_collection, build_knowledge_base with clear_existing=true). Tool names are reasonably action-oriented (build_, generate_, search_, add_, get_, clear_) but descriptions are sparse and sometimes ambiguous, e.g., 'Searches the knowledge base' doesn't explain when to use search vs generate_response.

• Document output schema for every tool. Example for search: 'Returns array of {document_id: string, content: string, source: string, similarity_score: number (0-1), metadata: {header?: string, type?: string}}.'
• Add confirmation step to clear_collection. Require a boolean 'confirm=true' parameter or return {status: 'pending_confirmation', message: 'This will delete all documents. Call with confirm=true to proceed.'}
• Define parameter constraints as JSON Schema with type, minimum, maximum, enum. Example: {"top_k": {"type": "integer", "minimum": 1, "maximum": 100, "default": 10}, "threshold": {"type": "number", "minimum": 0, "maximum": 1, "default": 0.25}}
• Clarify tool responsibilities with explicit descriptions. build_knowledge_base should state: 'Rebuilds the entire knowledge base from all .txt files in the txt directory, optionally clearing existing data first. Use this for initial setup or major refreshes. For incremental updates, use add_documents instead.'
• Add tool annotations via MCP: readOnlyHint=true for get_*, search, generate_response, process_documents, test_query; destructiveHint=true for clear_collection; idempotentHint=true for get_* tools.
• Move API_KEY from config.py to environment variable. Update RAGSystem.__init__ to read from os.environ['ALIYUN_API_KEY']. Never expose credentials in tool parameters.
• Add error handling stubs to each tool returning {status: 'error', code: string, message: string, suggestion: string}. Example: clear_collection error: {status: 'error', code: 'collection_empty', message: 'Collection already empty', suggestion: 'No action needed.'}