Loading ToolBench
MCP server for generating React Admin components, UX designs, and analyzing MongoDB schemas
Server has 8 tools with significant definition gaps. Tool names lack clear action verbs (analyzeSchema, generateDesign, generateDesignPrompt are vague). Most descriptions are present but generic (10-50 chars). Critical issue: 6 of 8 tools have empty input schemas ({}) or severely incomplete schemas missing parameter descriptions. generateDesign has a complex nested schema but no parameter descriptions. updateObject is the only tool with properly described parameters. No output schemas documented. Error handling is absent, no recovery guidance or actionable error messages visible in code.
Analyzes MongoDB schemas to generate architecture recommendations
Generates UX designs based on architecture and requirements.
Generates a comprehensive UX design prompt based on schema analysis.
Generate React-Admin components with various configurations
Generates a comprehensive prompt for React Admin component generation based on architecture and design specifications.
Retrieves multiple documents from a specified MongoDB collection.
Fetch all MongoDB collection schemas
6 of 8 tools have empty or missing input schemas. analyzeSchema, getSchemas have {} with no parameters documented. generateDesign has nested schema but zero parameter descriptions. LLMs cannot infer what inputs these tools accept.
Tool names lack action verbs. 'analyzeSchema', 'generateDesign', 'generateDesignPrompt' are vague. Should be 'analyze_mongodb_schema', 'generate_ux_design', 'generate_design_prompt' to clarify intent and enable LLM verb-based dispatch.
No output schemas documented for any tool. LLMs cannot plan downstream calls or extract required fields. generateDesign, generateReactAdminPrompt return complex nested structures with no field documentation.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 40 | 2026-07-28+ | v2 |
Updates a specific MongoDB document by its _id in a given collection.
No error handling or recovery guidance in any tool. Code has try-catch blocks that log errors but return no actionable messages to LLM. If analyzeSchema fails on a collection, agent has no guidance on what to do next.
Descriptions are too short (10-50 chars for most tools). 'Analyzes MongoDB schemas to generate architecture recommendations' (59 chars) lacks WHEN to use, WHAT it returns, and prerequisites. Baseline for A+ tools is 50-200 chars with explicit context.