deep_scan             Initial reconnaissance
                        |                Identifies 3-7 key findings
                        v                May ask clarifying questions
                   deep_explore          Recursive what-if chains
                  /     |     \          Loops until max depth
             Branch  Branch  Branch      Each gets mitigations + sub-findings
                  \     |     /
                        v
                  deep_synthesize        Action plan, residual risks,
                                         decision log, quick wins

pip install deep-reasoning-mcp

git clone https://github.com/yourusername/deep-reasoning-mcp.git
cd deep-reasoning-mcp
uv sync

{
  "mcpServers": {
    "deep-reasoning": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/deep-reasoning-mcp",
        "run",
        "deep-reasoning-mcp"
      ]
    }
  }
}

{
  "mcpServers": {
    "deep-reasoning": {
      "command": "deep-reasoning-mcp"
    }
  }
}

{
  "mcpServers": {
    "deep-reasoning": {
      "command": "deep-reasoning-mcp",
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}

Analyze the payment callback flow for race conditions.
Stack: Django 4.2, PostgreSQL, Celery, RabbitMQ.
PSPs send HTTP POST callbacks that can arrive within milliseconds of each other.

Payment callbacks timeout randomly after 30s under load.
Logs show the PSP responds in 2s. The issue started after last Thursday's deploy.
Stack: Django, Gunicorn (4 workers), PostgreSQL, Redis cache.

Production: ticket validation failing for operator CTM for ~20 minutes.
No recent deploys. Health checks pass. Grafana shows normal latency
but elevated 500s on the /api/v2/validate/ endpoint.

We're evaluating migrating from Celery to Django-Q2 for async tasks.
We have ~50 Celery tasks, some with complex retry logic, beat scheduling,
and chain/chord patterns. What are the trade-offs?

~/.claude/deep-reasoning/
  sessions/
    20250409_152030_debugging_payment_callback.json
    20250408_091500_architecture_auth_flow.json
  index.json

{
  "id": "a1b2c3d4",
  "version": "2.0",
  "analysis_type": "architecture",
  "max_depth": 3,
  "current_depth": 2,
  "status": "exploring",
  "language": "en",
  "description": "Original problem description",
  "findings": [
    {
      "id": "e5f6g7h8",
      "depth": 1,
      "status": "complete",
      "title": "Race condition on payment callback",
      "severity": "critical",
      "condition": "IF two callbacks arrive within 50ms for same transaction",
      "consequence": "THEN duplicate transaction record created",
      "mitigations": [
        {
          "action": "Add SELECT FOR UPDATE on transaction lookup",
          "where": "PaymentCallbackView.process_callback()",
          "risk_introduced": "Increased lock contention under high load",
          "effort": "medium"
        }
      ],
      "sub_findings": [
        {
          "id": "i9j0k1l2",
          "depth": 2,
          "status": "pending",
          "title": "Lock contention under peak load",
          "severity": "high",
          "condition": "IF >100 concurrent callbacks hit the same lock",
          "consequence": "THEN connection pool exhaustion, cascading timeouts"
        }
      ]
    }
  ],
  "metadata": {
    "total_findings": 5,
    "explored_findings": 3,
    "critical_count": 1,
    "high_count": 2
  }
}

deep_reasoning_mcp/
  __init__.py      # Package entry point
  server.py        # MCP tool handlers
  models.py        # Pydantic models and enums
  tree.py          # Reasoning tree helpers
  session.py       # Session persistence
  prompts.py       # Analysis-type-specific prompts
  llm.py           # Anthropic API client with rate limiting