A Model Context Protocol server that manages multiple specialized MCPs (Research and Webscraping) and routes user requests to the appropriate handler based on content analysis.
Critical failures across all dimensions. The server defines 6 tools but exhibits severe duplication (generate_question and generate_response appear 3 times each with identical signatures). No input schemas are visible in the source code, only parameter names and basic type hints. Descriptions are generic and under 20 characters for most tools. No output schemas documented. No error handling guidance. Tool names lack action verbs (generate_question/generate_response are vague; unclear what 'generate' means in context). Parameters lack descriptions explaining their purpose or constraints. No evidence of idempotency, pagination, or composition patterns. The codebase shows a basic interactive CLI loop, not a production MCP server with proper tool registration.
Generate a clarifying question based on the user's webscraping request
Generate a clarifying question based on the user's research request
Generate a clarifying question based on the user's webscraping request
Generate a research response based on the original request and the user's answer
Generate a webscraping response based on the original request and the user's answer
Generate a webscraping response based on the original request and the user's answer
No input schemas visible in source code. Tools declare only parameter names ('user_input', 'original_request', 'user_answer') with type hints but no JSON Schema definitions.
Duplicate tool definitions. generate_question and generate_response each appear 3 times with identical signatures. LLMs cannot disambiguate between research vs webscraping variants. Violates single-responsibility principle.
Descriptions are generic and under 20 characters. 'Generate a clarifying question based on the user's research request' (68 chars) lacks WHEN to use, WHAT it returns, and HOW it differs from webscraping variant.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 19 | <=2025-11-25 | v2 |
No output schemas documented. Tools return strings but LLMs cannot plan downstream calls or extract structured data. No pagination, no error classification, no recovery guidance.
Tool names lack action verbs. 'generate_question' and 'generate_response' are vague, does 'generate' mean create, fetch, compute, or synthesize? Verb_noun pattern (e.g. ask_clarifying_question, create_response) would be clearer.