get_user_context
Retrieve stored user facts, patterns, and preferences to personalize responses and support ADHD productivity coaching.
Instructions
Get relevant context about the user (facts, patterns, preferences).
This retrieves stored facts about the user to help personalize responses.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- src/coach_ai/server.py:594-599 (handler)The MCP tool definition for 'get_user_context' which delegates to the storage layer.
async def get_user_context() -> str: """Get relevant context about the user (facts, patterns, preferences). This retrieves stored facts about the user to help personalize responses. """ return await storage.get_user_context() - src/coach_ai/storage.py:356-388 (handler)The actual implementation of the 'get_user_context' tool logic, which queries the 'user_facts' database table and formats the retrieved data.
async def get_user_context() -> str: """Get relevant context about the user. Returns: Formatted user context """ db = await get_db() cursor = await db.execute( "SELECT fact, category FROM user_facts ORDER BY created_at DESC LIMIT 20" ) rows = await cursor.fetchall() if not rows: return "No user facts stored yet. Use add_user_fact() to remember important information." result = "\n=== USER CONTEXT ===\n\n" # Group by category categories = {} for row in rows: cat = row["category"] if cat not in categories: categories[cat] = [] categories[cat].append(row["fact"]) for category, facts in categories.items(): result += f"{category.upper()}:\n" for fact in facts: result += f" - {fact}\n" result += "\n" return result.strip()