This MCP server has severe definition quality issues across all three tools. None of the tools have visible input schemas in the provided source code. Tool descriptions exist but are superficial (YouTube: 103 chars, Drive: 98 chars, Notion: 106 chars, all below the baseline 194 chars average). Parameters are completely undocumented. The tools appear to be called via Pipedream webhook URLs rather than through properly structured MCP tool registration with JSON Schema input/output definitions. No evidence of parameter type definitions, enums, validation rules, or output schemas. The architecture appears to delegate tool execution to external Pipedream workflows, which means the MCP server itself is not defining or validating tool contracts, it is merely routing to HTTP endpoints. This architectural pattern violates the fundamental MCP design principle that tools should have self-documenting, complete schema definitions.

• Define explicit JSON Schema input and output schemas for each tool. Example: youtube tool should accept {type: 'object', properties: {query: {type: 'string', description: 'Search term for YouTube videos'}, max_results: {type: 'integer', minimum: 1, maximum: 50}, ...}} and return {videos: [{video_id, title, duration, channel, url}], total_count, next_cursor}.
• Rename tools to action-verb form: 'search_youtube', 'create_google_drive_document', 'create_notion_page'. This makes intent clear at a glance.
• Expand tool descriptions to 150-250 characters explaining WHAT the tool does, WHEN to use it instead of alternatives, and WHAT it returns. Example: 'Search YouTube for educational videos matching a query. Returns up to 50 results with titles, durations, and URLs. Use this to find learning resources for each day of the path. Does NOT create playlists; use create_youtube_playlist after identifying videos.'
• Document every parameter with type, format, and constraints. Example: youtube search query parameter should be '{type: "string", minLength: 1, maxLength: 200, description: "Search query (e.g. \'Python basics tutorial\')"}'.
• Move API credentials (Google API key, Pipedream URLs) out of the Streamlit UI and into environment variables. Update the server to read GOOGLE_API_KEY, YOUTUBE_PIPEDREAM_URL, DRIVE_PIPEDREAM_URL, NOTION_PIPEDREAM_URL from process.env. This prevents credential leakage in logs and UI traces.
• Add error handling patterns. Each tool should catch Pipedream HTTP failures and return structured errors like {error: 'rate_limited', message: 'YouTube API quota exceeded. Try again in 1 hour.', recovery: 'Wait before retrying or use a cached result.'} instead of raw HTTP 429 responses.