MCP server for the Brain Researcher platform, providing tools for neuroimaging analysis, knowledge graph exploration, and research workflow orchestration
Single tool 'fetchKGTools' has a well-structured input schema with 7 parameters, all typed and described. However, the tool definition is inferred from a React component file (ToolsBrowserDrawer.tsx), not from explicit MCP server registration code. No output schema is documented. The description is adequate (89 chars) but lacks guidance on when to use this tool vs alternatives, what structure is returned, or error recovery. The tool name 'fetchKGTools' uses a verb but is somewhat generic ('fetch' could mean HTTP GET, database query, or cache lookup). No evidence of error handling, validation, or response shaping in the provided source.
Fetch tools from the knowledge graph for a given operation, with optional filtering by exposure level, domain, function, and risk
Tool definition inferred from React component, not explicit MCP server registration. No visible tool registration in Python MCP server code.
No output schema documented. LLMs cannot plan downstream calls or extract required fields (e.g., tool IDs, names, metadata structure).
Description lacks context on when to use this tool, what structure is returned, and how to handle errors. Does not answer: What does it return? When should I call it?
No error handling guidance. If operation is invalid, domain filter fails, or knowledge graph is unavailable, LLM has no recovery path.
Tool name 'fetchKGTools' is generic. 'fetch' does not clearly distinguish this from other discovery tools. Consider 'search_kg_tools' or 'list_kg_tools_by_operation'.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 42 | 2026-07-28+ | v2 |