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ai/doc/agent_harness_flow.md

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┌─────────────────────────────────────────────────┐
│ Agent Harness (your servers) │
│ │
│ on_message(user_id, message): │
│ 1. Look up user's MCP endpoint from Postgres │
│ 2. mcp.call("get_context_summary") │
│ 3. mcp.call("get_conversation_history", 20) │
│ 4. Build prompt: │
│ system = BASE_PROMPT │
│ + context_summary │
│ + user_agent_prompt (from MCP) │
│ messages = history + new message │
│ 5. LLM call (your API key) │
│ 6. While LLM wants tool calls: │
│ - Platform tools → handle locally │
│ - User tools → proxy to MCP │
│ - LLM call again with results │
│ 7. mcp.call("save_message", ...) │
│ 8. Return response to user │
│ │
└─────────────────────────────────────────────────┘