lutflow-mcp

# Lutflow MCP Server **The first AI FinOps tool with native MCP support.** Works inside Cursor, Claude Code, VS Code, and any MCP-compatible client. ## Installation ```bash pip install lutflow-mcp ``` Or install from source: ```bash cd mcp-server pip install -e . ``` ## Configuration ### For Cursor Add to your `~/.cursor/mcp.json`: ```json { "mcpServers": { "lutflow": { "command": "lutflow-mcp", "env": { "LUTFLOW_API_KEY": "lut_xxx", "LUTFLOW_TENANT_ID": "your-tenant" } } } } ``` ### For Claude Desktop Add to your Claude Desktop config: ```json { "mcpServers": { "lutflow": { "command": "lutflow-mcp", "env": { "LUTFLOW_API_KEY": "lut_xxx" } } } } ``` ## Available Tools ### 1. `check_budget` Check current budget status for a tenant. ``` check_budget(tenant_id="acme") ``` Returns: budget limit, spent amount, remaining budget, utilization percentage. ### 2. `list_deployments` List all active AI model deployments. ``` list_deployments(tenant_id="acme") ``` Returns: deployment IDs, models, costs, status, kill path state. ### 3. `get_costs` Get detailed cost breakdown by model and deployment. ``` get_costs(period="today") get_costs(deployment_id="abc-123", period="week") ``` Returns: total spend, per-model costs, billing event count. ### 4. `kill_deployment` Manually terminate an AI model deployment. ``` kill_deployment(deployment_id="abc-123", reason="overspend") ``` Triggers the Lutflow kill path (eBPF → Tetragon → kubectl fallback). ### 5. `recommend_model` Get AI model recommendation for a task within budget. ``` recommend_model(task="text-classification", budget_usd_per_hour=0.50) recommend_model(task="code-generation", gpu_type="nvidia-a100-80gb") ``` Uses live HuggingFace benchmark data and real-time GPU pricing. ## Environment Variables | Variable | Description | Default | |----------|-------------|---------| | `LUTFLOW_API_KEY` | API key for Lut…