MCP Server
Prefect MCP Server
A Model Context Protocol server that allows AI assistants to interact with Prefect's workflow automation platform through natural language, enabling users to manage flows, deployments, tasks, and other Prefect resources via conversational commands.
14
GitHub Stars
11/22/2025
Last Updated
MCP Server Configuration
1{
2 "name": "prefect",
3 "command": "mcp-prefect",
4 "args": [
5 "--transport",
6 "stdio"
7 ]
8}
JSON8 lines
README Documentation
Prefect MCP Server
A Model Context Protocol (MCP) server implementation for Prefect, enabling AI assistants to interact with Prefect through natural language.
Note: The official Prefect MCP server is available here. This is a community implementation.
๐ Quick Start
docker compose up
๐ฆ Installation
pip Installation
pip install mcp-prefect
From Source
git clone https://github.com/allen-munsch/mcp-prefect
cd mcp-prefect
pip install -e .
Manual Run
PREFECT_API_URL=http://localhost:4200/api \
PREFECT_API_KEY=your_api_key_here \
MCP_PORT=8000 \
python -m mcp_prefect.main --transport http
๐ ๏ธ Features
โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ โ
โ _ __ ___ _____ __ __ _____________ ____ ____ โ
โ _ __ ___ .'____/___ ______/ /_/ |/ / ____/ __ \ |___ \ / __ \ โ
โ _ __ ___ / /_ / __ `/ ___/ __/ /|_/ / / / /_/ / ___/ / / / / / โ
โ _ __ ___ / __/ / /_/ (__ ) /_/ / / / /___/ ____/ / __/_/ /_/ / โ
โ _ __ ___ /_/ \____/____/\__/_/ /_/\____/_/ /_____(*)____/ โ
โ โ
โ โ
โ FastMCP 2.0 โ
โ โ
โ โ
โ ๐ฅ๏ธ Server name: MCP Prefect 3.6.1 โ
โ ๐ฆ Transport: STDIO โ
โ โ
โ ๐๏ธ FastMCP version: 2.12.3 โ
โ ๐ค MCP SDK version: 1.14.1 โ
โ โ
โ ๐ Docs: https://gofastmcp.com โ
โ ๐ Deploy: https://fastmcp.cloud โ
โ โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
[11/11/25 02:08:06] INFO Starting MCP server 'MCP Prefect 3.6.1' with transport 'stdio' server.py:1495
โ
Initialized successfully
Server: MCP Prefect 3.6.1 1.14.1
๐ Listing tools...
๐ฏ FOUND 64 TOOLS:
================================================================================
๐ ARTIFACT (6 tools)
๐ง create_artifact
๐ง delete_artifact
๐ง get_artifact
๐ง get_artifacts
๐ง get_latest_artifacts
๐ง update_artifact
๐ AUTOMATION (7 tools)
๐ง create_automation
๐ง delete_automation
๐ง get_automation
๐ง get_automations
๐ง pause_automation
๐ง resume_automation
๐ง update_automation
๐ BLOCK (5 tools)
๐ง delete_block_document
๐ง get_block_document
๐ง get_block_documents
๐ง get_block_type
๐ง get_block_types
๐ DEPLOYMENT (8 tools)
๐ง delete_deployment
๐ง get_deployment
๐ง get_deployment_schedule
๐ง get_deployments
๐ง pause_deployment_schedule
๐ง resume_deployment_schedule
๐ง set_deployment_schedule
๐ง update_deployment
๐ FLOW (13 tools)
๐ง cancel_flow_run
๐ง create_flow_run_from_deployment
๐ง delete_flow
๐ง delete_flow_run
๐ง get_flow
๐ง get_flow_run
๐ง get_flow_run_logs
๐ง get_flow_runs
๐ง get_flow_runs_by_flow
๐ง get_flows
๐ง get_task_runs_by_flow_run
๐ง restart_flow_run
๐ง set_flow_run_state
๐ LOG (2 tools)
๐ง create_log
๐ง get_logs
๐ OTHER (1 tools)
๐ง get_health
๐ TASK (4 tools)
๐ง get_task_run
๐ง get_task_run_logs
๐ง get_task_runs
๐ง set_task_run_state
๐ VARIABLE (5 tools)
๐ง create_variable
๐ง delete_variable
๐ง get_variable
๐ง get_variables
๐ง update_variable
๐ WORK (13 tools)
๐ง create_work_queue
๐ง delete_work_queue
๐ง get_current_workspace
๐ง get_work_queue
๐ง get_work_queue_by_name
๐ง get_work_queue_runs
๐ง get_work_queues
๐ง get_workspace
๐ง get_workspace_by_handle
๐ง get_workspaces
๐ง pause_work_queue
๐ง resume_work_queue
๐ง update_work_queue
๐ TOTAL: 64 tools across 10 categories
๐ฌ 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"
๐ค Platform Integration
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"prefect": {
"command": "mcp-prefect",
"args": ["--transport", "stdio"]
}
}
}
Cursor MCP
{
"mcpServers": {
"prefect": {
"command": "mcp-prefect",
"args": ["--transport", "stdio"]
}
}
}
Gemini CLI
gemini config set mcp-servers.prefect "mcp-prefect --transport stdio"
Windsurf / Claude Code
{
"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
{
"mcpServers": {
"prefect": {
"command": "mcp-prefect",
"args": ["--transport", "stdio"],
"env": {
"PREFECT_API_URL": "http://localhost:4200/api",
"PREFECT_API_KEY": "your_api_key_here"
}
}
}
}
๐งช Development
Running Tests
pytest tests/ -v
Building from Source
git clone https://github.com/allen-munsch/mcp-prefect
cd mcp-prefect
pip install -e .
python -m mcp_prefect
Quick Install
Quick Actions
Key Features
Model Context Protocol
Secure Communication
Real-time Updates
Open Source