Prefect

Prefect

MCP server for Prefect enabling AI assistants to interact with Prefect through natural language.

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Overview

This is a community MCP server implementation for Prefect that enables AI assistants to interact with Prefect via natural language. It connects to Prefect Server or Prefect Cloud through the Prefect API (via PREFECT_API_URL and PREFECT_API_KEY) and exposes a broad set of MCP endpoints that map to Prefect resources and actions. The server enumerates 64 tools across 10 categories (ARTIFACT, AUTOMATION, BLOCK, DEPLOYMENT, FLOW, LOG, OTHER, TASK, VARIABLE, WORK), including operations to create, get, update, and delete artifacts, automations, blocks, deployments, flows, logs, task runs, variables, and work queues. Transport is STDIO, enabling embedding in AI chat clients or CLI workflows. A Docker Compose quick-start and runtime configuration via environment variables (PREFECT_API_URL, PREFECT_API_KEY, MCP_PORT) simplify setup. Example interactions illustrate natural-language requests for Flow management, Deployment control, Infrastructure management, Variable handling, and Log monitoring. Platform integrations cover Claude Desktop, Cursor MCP, Gemini CLI, Windsurf/Claude Code, and Generic MCP Client. This community server is offered as an alternative to the official prefect-mcp package and provides documentation and deployment resources.

Details

Owner
allen-munsch
Language
Python
License
Apache License 2.0
Updated
2025-12-07

Features

Extensive tool catalog across 10 categories

Exposes 64 tools grouped into ARTIFACT, AUTOMATION, BLOCK, DEPLOYMENT, FLOW, LOG, OTHER, TASK, VARIABLE, and WORK, enabling full Prefect resource control via MCP.

Prefect API integration

Connects to Prefect Server/Cloud via the Prefect API using PREFECT_API_URL and PREFECT_API_KEY, supporting operations on artifacts, flows, deployments, tasks, variables, and more.

STDIO transport

Operates over STDIO to simplify embedding in AI assistants and CLI workflows.

Docker Quick Start

Docker Compose provides a quick path to deploy the MCP Prefect server.

Configurable runtime via environment variables

Runtime configuration supports MCP_PORT, PREFECT_API_URL, and PREFECT_API_KEY via environment variables.

Cross-platform integrations

Platform integrations shown include Claude Desktop, Cursor MCP, Gemini CLI, Windsurf/Claude Code, and Generic MCP Client using standard MCP config.

Natural language interactions for common workflows

Supports conversational prompts for Flow Management, Deployment Control, Infrastructure Management, Variable handling, and Monitoring.

Community-driven with documentation links

Community implementation with references to official docs, deployment resources, and platform integration examples.

Audience

AI assistantsEnable AI agents to manage Prefect resources via natural language using MCP.
DevelopersIntegrate Prefect workflows with AI copilots via MCP for automation and orchestration.

Tags

prefectmcpworkflow orchestrationELT/ETLai assistantsnatural languagestdiodockerintegration