The server exposes 2 tools with basic schemas and descriptions. However, both tools suffer from significant definition gaps: descriptions lack depth and context for LLM decision-making, parameter constraints are absent (e.g., no bounds on top_k, no guidance on image encoding), output schemas are documented in docstrings but lack formal JSON Schema structure, and error handling is minimal. Tool naming follows verb_noun convention (search-based), which is positive, but the overall definitions fall well below production readiness for agent deployment. The server is HTTP-based (FastMCP framework), which supports modern transport, but the tool definitions themselves are underdeveloped.

• Add explicit parameter constraints: top_k should have minimum=1, maximum=100 (or server-appropriate limit), and default=10. 'image_query' should specify base64 encoding in the schema format field or as a JSON Schema 'format' constraint.
• Expand tool descriptions to 150 - 250 characters. Include WHEN to use each tool: 'Use this tool to search for visually similar images when you have an image file. Use text_to_image_search_tool for text-based queries.' Add prerequisite: 'Requires ChromaDB collection to be initialized and loaded.'
• Define and return formal output schemas. Register tools with explicit response schemas listing fields (metadata, base64_image) and their types. Example: { type: 'array', items: { type: 'object', properties: { metadata: {type: 'object'}, base64_image: {type: 'string'} } } }
• Implement structured error handling. Wrap both tools in try/catch blocks. Return error objects with code, message, and recovery hint: { error: 'collection_not_found', message: '...', recovery: 'Call initialize_chroma_collection() first' }. Never silently return empty results.
• Add parameter descriptions that include valid ranges and examples. E.g., top_k: 'Number of results to return (1-100, default 10). Larger values increase response tokens and may degrade LLM reasoning.'
• Consider adding a third discovery tool, list_available_collections(), to help agents explore ChromaDB without blind guessing. Include collection_name, description, and item_count.
• Document the relationship between the two tools in both descriptions: 'For visual similarity, use image_to_image_search_tool. For text-based search, use text_to_image_search_tool. Both return ranked results with base64-encoded images and metadata.'

Inferred effective spec: 2025-06-18+.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry