Prefect MCP Server

# Prefect MCP Server A Model Context Protocol (MCP) server implementation for [Prefect](https://www.prefect.io/), enabling AI assistants to interact with Prefect through natural language. > **Note**: The official Prefect MCP server is available [here](https://pypi.org/project/prefect-mcp/). This is a community implementation. ## 🚀 Quick Start ```bash docker compose up ``` ## 📦 Installation ### pip Installation ```bash pip install mcp-prefect ``` ### From Source ```bash git clone https://github.com/allen-munsch/mcp-prefect cd mcp-prefect pip install -e . ``` ### Manual Run ```bash PREFECT_API_URL=http://localhost:4200/api \ PREFECT_API_KEY=your_api_key_here \ MCP_PORT=8000 \ python -m mcp_prefect.main --transport http ``` ## 🛠️ Features ``` ╭────────────────────────────────────────────────────────────────────────────╮ │ │ │ _ __ ___ _____ __ __ _____________ ____ ____ │ │ _ __ ___ .'____/___ ______/ /_/ |/ / ____/ __ \ |___ \ / __ \ │ │ _ __ ___ / /_ / __ `/ ___/ __/ /|_/ / / / /_/ / ___/ / / / / / │ │ _ __ ___ / __/ / /_/ (__ ) /_/ / / / /___/ ____/ / __/_/ /_/ / │ │ _ __ ___ /_/ \____/____/\__/_/ /_/\____/_/ /_____(*)____/ │ │ │ │ │ │ FastMCP 2.0 │ │ │ │ │ │ 🖥️ Server name: MCP Prefect 3.6.1 │ │ 📦 Transport: STDIO │ │ │ │ 🏎️ FastMCP version: 2.12.3 │ │ 🤝 MCP SDK version: 1.14.1 │ │ │ │ 📚 Docs: https://gofastmcp.com │ │ 🚀 Deploy: https://fastmcp.cloud │ │ │ ╰────────────────────────────────────────────────────────────────────────────╯ [11/11/25 02:08:06] INFO Starting MCP server 'MCP Prefect 3.6.1' with transport 'stdio' server.py:1495 ✅ Initialized successfully Server: MCP Prefect 3.6.1 1.14.1 🔄 Listing tools... 🎯 FOUND 64 TOOLS: ================================================================================ 📂 ARTIFACT (6 tools) 🔧 create_artifact 🔧 delete_artifact 🔧 get_artifact 🔧 get_artifacts 🔧 get_latest_artifacts 🔧 update_artifact 📂 AUTOMATION (7 tools) 🔧 create_automation 🔧 delete_automation 🔧 get_automation 🔧 get_automations 🔧 pause_automation 🔧 resume_automation 🔧 update_automation 📂 BLOCK (5 tools) 🔧 delete_block_document 🔧 get_block_document 🔧 get_block_documents 🔧 get_block_type 🔧 get_block_types 📂 DEPLOYMENT (8 tools) 🔧 delete_deployment 🔧 get_deployment 🔧 get_deployment_schedule 🔧 get_deployments 🔧 pause_deployment_schedule 🔧 resume_deployment_schedule 🔧 set_deployment_schedule 🔧 update_deployment 📂 FLOW (13 tools) 🔧 cancel_flow_run 🔧 create_flow_run_from_deployment 🔧 delete_flow 🔧 delete_flow_run 🔧 get_flow 🔧 get_flow_run 🔧 get_flow_run_logs 🔧 get_flow_runs 🔧 get_flow_runs_by_flow 🔧 get_flows 🔧 get_task_runs_by_flow_run 🔧 restart_flow_run 🔧 set_flow_run_state 📂 LOG (2 tools) 🔧 create_log 🔧 get_logs 📂 OTHER (1 tools) 🔧 get_health 📂 TASK (4 tools) 🔧 get_task_run 🔧 get_task_run_logs 🔧 get_task_runs 🔧 set_task_run_state 📂 VARIABLE (5 tools) 🔧 create_variable 🔧 delete_variable 🔧 get_variable 🔧 get_variables 🔧 update_variable 📂 WORK (13 tools) 🔧 create_work_queue 🔧 delete_work_queue 🔧 get_current_workspace 🔧 get_work_queue 🔧 get_work_queue_by_name 🔧 get_work_queue_runs 🔧 get_work_queues 🔧 get_workspace 🔧 get_workspace_by_handle 🔧 get_workspaces 🔧 pause_work_queue 🔧 resume_work_queue 🔧 update_work_queue 📊 TOTAL: 64 tools across 10 categories ``` ## 💬 Example Interactions AI assistants can help you with: **Flow Management** - "Show me all my flows and their last run status" - "Create a new flow run for the 'data-processing' deployment" - "What's the current status of flow run 'abc-123'?" **Deployment Control** - "Pause the schedule for the 'daily-reporting' deployment" - "Update the 'etl-pipeline' deployment with new parameters" **Infrastructure Management** - "List all work pools and their current status" - "Create a new work queue for high-priority jobs" **Variable & Configuration** - "Create a variable called 'api_timeout' with value 300" - "Show me all variables containing 'config' in their name" **Monitoring & Debugging** - "Get the logs for the last failed flow run" - "Show me all running task runs right now" ## 🤖 Platform Integration ### Claude Desktop Add to `claude_desktop_config.json`: ```json { "mcpServers": { "prefect": { "command": "mcp-prefect", "args": ["--transport", "stdio"] } } } ``` ### Cursor MCP ```json { "mcpServers": { "prefect": { "command": "mcp-prefect", "args": ["--transport", "stdio"] } } } ``` ### Gemini CLI ```bash gemini config set mcp-servers.prefect "mcp-prefect --transport stdio" ``` ### Windsurf / Claude Code ```json { "mcpServers": { "prefect": { "command": "mcp-prefect", "args": ["--transport", "stdio"], "env": { "PREFECT_API_URL": "http://localhost:4200/api", "PREFECT_API_KEY": "your_api_key_here" } } } } ``` ### Generic MCP Client ```json { "mcpServers": { "prefect": { "command": "mcp-prefect", "args": ["--transport", "stdio"], "env": { "PREFECT_API_URL": "http://localhost:4200/api", "PREFECT_API_KEY": "your_api_key_here" } } } } ``` ## 🧪 Development ### Running Tests ```bash pytest tests/ -v ``` ### Building from Source ```bash git clone https://github.com/allen-munsch/mcp-prefect cd mcp-prefect pip install -e . python -m mcp_prefect ```