How to use the Prefect MCP server

The Prefect MCP server enables AI assistants to interact with your Prefect workflows and infrastructure through the Model Context Protocol (MCP). This integration allows AI tools like Claude Code, Cursor, and Codex CLI to help you monitor deployments, debug flow runs, query infrastructure, and more.

The Prefect MCP server is currently in beta. APIs, features, and behaviors may change without notice. We encourage you to try it out and provide feedback through GitHub issues.

What is the Prefect MCP server?

The Prefect MCP server is an MCP server that provides AI assistants with tools to:

Monitor & inspect: View system health, query deployments, flow runs, task runs, work pools, and execution logs
Debug intelligently: Get contextual guidance for troubleshooting failed flows and deployment issues
Access documentation: Query up-to-date Prefect documentation through an integrated docs proxy

The MCP tools are primarily designed for reading data and monitoring your Prefect instance. For creating or updating resources, the integrated docs proxy provides AI assistants with current information on how to use the prefect CLI.

Security considerations

The Prefect MCP server provides read-only access to your Prefect instance. It can only access information available to the account you authenticate with—it cannot access data outside those bounds.

Important: The MCP server does not operate in isolation. MCP clients (such as Claude Code, Cursor, or Codex CLI) may have additional capabilities beyond the MCP server’s read-only tools. For example, an AI assistant with terminal access could execute destructive CLI commands like prefect deployment delete independently of the MCP server.When using AI agents autonomously, consider the Prefect Role associated with your API key and what actions the agent could take through other means (CLI, SDK, etc.).

For detailed answers to common security questions—including authentication patterns, RBAC, file access requirements, and recommendations for internal pilots—see the Security FAQ.

Installation

Connect ChatGPT or Claude to Prefect Cloud

Use the Prefect plugin in ChatGPT or the Prefect connector in Claude to connect to Prefect’s hosted MCP server. You need an account in your chosen assistant and access to a Prefect Cloud workspace. No local installation, API key, or server deployment is required.

ChatGPT plugin
Claude connector

Open the Prefect plugin listing and install it.
Start a chat with Prefect selected and follow the Connect prompt to sign in to Prefect Cloud.
Select the workspaces ChatGPT may read and authorize the connection.

Installing the plugin and connecting your account are separate steps. If an existing chat does not discover the newly connected tools, start a fresh chat with Prefect selected.

Ask “Which Prefect workspaces can you access?” Then name a workspace and ask “Why did my most recent failed flow run fail?” The hosted tools inspect runs, logs, and workspace health and search Prefect documentation. They are read-only, and workspace access is limited to the workspaces selected during authorization. For self-hosted Prefect, use a local installation or deploy your own MCP server as described below.

Local installation

Install and run the MCP server locally using uvx:

uvx --from prefect-mcp prefect-mcp-server

When running locally with stdio transport, the server automatically inherits credentials from your active Prefect profile (~/.prefect/profiles.toml).

Cloud deployment

Deploy the MCP server to Prefect Horizon for remote access:

Fork the prefect-mcp-server repository on GitHub
Sign in to horizon.prefect.io
Create a new server pointing to your fork:
- Server path: src/prefect_mcp_server/server.py
- Requirements: pyproject.toml (or leave blank)

Configure environment variables in the Prefect Horizon interface:

Environment Variable	Prefect Cloud	Self-hosted Prefect
`PREFECT_API_URL`	`https://api.prefect.cloud/api/` `accounts/[ACCOUNT_ID]/` `workspaces/[WORKSPACE_ID]`	Your Prefect server URL (e.g., `http://your-server:4200/api`)
`PREFECT_API_KEY`	Your Prefect Cloud API key	Not used
`PREFECT_API_AUTH_STRING`	Not used	Your authentication string (if using basic auth)

Get your server URL (e.g., https://your-server-name.fastmcp.app/mcp)

When deploying to Prefect Horizon, environment variables are configured on the Prefect Horizon server itself (step 4 above), not in your client configuration. FastMCP’s authentication secures access to your MCP server, while the MCP server uses your Prefect API key to access your Prefect instance.

Prefect Cloud users on Team, Pro, and Enterprise plans can use service accounts for API authentication. Pro and Enterprise users can restrict service accounts to read-only access (only see_* permissions) since the Prefect MCP server requires no write permissions.

Client setup

Configure your AI assistant to connect to the Prefect MCP server.

General setup

For local stdio connections, MCP clients need three pieces of information:

Command: uvx
Arguments: --from prefect-mcp prefect-mcp-server
Environment variables (optional): Credentials for your Prefect instance

The configuration format varies by client. Choose your client below for specific setup instructions:

Claude Code

Marketplace install (recommended)The easiest way to get started with Claude Code is through the plugin marketplace:

# Add from marketplace
/plugin marketplace add prefecthq/prefect-mcp-server

# Install the plugin
/plugin install prefect

The plugin connects to Prefect’s hosted, read-only MCP server and includes workflow guidance for diagnostics, documentation, and release notes. Sign in to Prefect Cloud through OAuth and select the workspaces Claude Code may access.

The hosted plugin does not use your local Prefect profile or require a local Prefect installation. For self-hosted Prefect or explicit credentials, use the manual setup below.

Manual setupAlternatively, add the Prefect MCP server to Claude Code using the CLI:

# Minimal setup - inherits from local Prefect profile
claude mcp add prefect -- uvx --from prefect-mcp prefect-mcp-server

# With explicit Prefect Cloud credentials
claude mcp add prefect \
  -e PREFECT_API_URL=https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID] \
  -e PREFECT_API_KEY=your-cloud-api-key \
  -- uvx --from prefect-mcp prefect-mcp-server

# With Prefect Horizon deployment (HTTP transport)
claude mcp add prefect --transport http https://your-server-name.fastmcp.app/mcp

Cursor

Add the Prefect MCP server to Cursor by creating or editing .cursor/mcp.json in your project:

{
  "mcpServers": {
    "prefect": {
      "command": "uvx",
      "args": ["--from", "prefect-mcp", "prefect-mcp-server"]
    }
  }
}

To use explicit credentials, add an env section:

{
  "mcpServers": {
    "prefect": {
      "command": "uvx",
      "args": ["--from", "prefect-mcp", "prefect-mcp-server"],
      "env": {
        "PREFECT_API_URL": "https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID]",
        "PREFECT_API_KEY": "your-cloud-api-key"
      }
    }
  }
}

Codex CLI

Add the Prefect MCP server to Codex using the CLI:

# Minimal setup - inherits from local Prefect profile
codex mcp add prefect -- uvx --from prefect-mcp prefect-mcp-server

# With explicit Prefect Cloud credentials
codex mcp add prefect \
  --env PREFECT_API_URL=https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID] \
  --env PREFECT_API_KEY=your-cloud-api-key \
  -- uvx --from prefect-mcp prefect-mcp-server

Alternatively, edit ~/.codex/config.toml directly:

[mcp.prefect]
command = "uvx"
args = ["--from", "prefect-mcp", "prefect-mcp-server"]

# For explicit credentials, add:
[mcp.prefect.env]
PREFECT_API_URL = "https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID]"
PREFECT_API_KEY = "your-cloud-api-key"

Gemini CLI

Add the Prefect MCP server to Gemini CLI using the CLI:

# STDIO transport - runs locally with uvx
gemini mcp add prefect uvx --from prefect-mcp prefect-mcp-server

# With explicit Prefect Cloud credentials
gemini mcp add prefect \
  -e PREFECT_API_URL=https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID] \
  -e PREFECT_API_KEY=your-cloud-api-key \
  uvx --from prefect-mcp prefect-mcp-server

# HTTP transport - for Prefect Horizon deployment
gemini mcp add prefect --transport http https://your-server-name.fastmcp.app/mcp

Alternatively, edit ~/.gemini/settings.json directly:For STDIO transport (local):

{
  "mcpServers": {
    "prefect": {
      "command": "uvx",
      "args": ["--from", "prefect-mcp", "prefect-mcp-server"]
    }
  }
}

For STDIO transport with explicit credentials:

{
  "mcpServers": {
    "prefect": {
      "command": "uvx",
      "args": ["--from", "prefect-mcp", "prefect-mcp-server"],
      "env": {
        "PREFECT_API_URL": "https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID]",
        "PREFECT_API_KEY": "your-cloud-api-key"
      }
    }
  }
}

For HTTP transport (Prefect Horizon):

{
  "mcpServers": {
    "prefect": {
      "httpUrl": "https://your-server-name.fastmcp.app/mcp"
    }
  }
}

Credentials configuration

The Prefect MCP server authenticates with your Prefect instance using the same configuration as the Prefect SDK.

Default behavior

When running locally without environment variables, the server inherits credentials from your active Prefect profile:

Profile configuration: ~/.prefect/profiles.toml
Uses the same API URL and authentication as your current prefect CLI commands

Environment variables

Override the default credentials by setting environment variables: For Prefect Cloud:

PREFECT_API_URL=https://api.prefect.cloud/api/accounts/[ACCOUNT_ID]/workspaces/[WORKSPACE_ID]
PREFECT_API_KEY=your-cloud-api-key

For self-hosted Prefect with basic auth:

PREFECT_API_URL=http://your-server:4200/api
PREFECT_API_AUTH_STRING=your-auth-string

Find your account ID and workspace ID in your Prefect Cloud browser URL:https://app.prefect.cloud/account/[ACCOUNT-ID]/workspace/[WORKSPACE-ID]/dashboard

Credential precedence

Environment variables take precedence over profile settings:

Environment variables (PREFECT_API_URL, PREFECT_API_KEY)
Active Prefect profile (~/.prefect/profiles.toml)

Available capabilities

The Prefect MCP server provides these main capabilities:

Read-only monitoring & inspection

View dashboard overviews with flow run statistics and work pool status
Query deployments, flow runs, task runs, and work pools with advanced filtering
Retrieve detailed execution logs from flow runs
Track events across your workflow ecosystem
Review automations and their configurations

Intelligent debugging

Get contextual guidance for troubleshooting failed flow runs
Diagnose deployment issues including concurrency problems
Identify root causes of workflow failures
Analyze rate limiting issues (Prefect Cloud only)

Documentation access

The MCP server includes a built-in docs proxy that provides AI assistants with up-to-date information from the Prefect documentation. This enables your AI assistant to:

Look up current API syntax and usage patterns
Find the correct prefect CLI commands for creating and updating resources
Access the latest best practices and examples

Mutations via CLI or SDK

The MCP tools are read-only. For create/update operations, use prefect CLI or SDK commands (often guided by docs proxy lookups).

Prompting tips

To get the most out of the Prefect MCP server, guide your AI assistant with these patterns:

Use the prefect CLI for write operations

The MCP tools are optimized for reading and monitoring. For creating or updating resources, prompt your assistant to use the prefect CLI: Example prompts:

“Use the prefect CLI to create a new deployment”
“Show me how to update this deployment’s schedule using prefect”
“Create an automation using the prefect CLI”

Leverage the docs proxy

The integrated docs proxy gives your assistant access to current Prefect documentation: Example prompts:

“Look up the latest syntax for creating a work pool”
“Find documentation on how to configure Docker work pools”
“What are the current best practices for deployment configuration?”

Ask diagnostic questions

The MCP server excels at helping diagnose issues: Example prompts:

“Why is my deployment not running?”
“Debug the last failed flow run”
“Why are my flow runs delayed?”
“Show me which work pools have no active workers”

Workflows

Deployments

Configuration

Automations

Workflow Infrastructure

Prefect Cloud

Prefect Self-hosted

AI

Migrate

How to use the Prefect MCP server

What is the Prefect MCP server?

Security considerations

Installation

Connect ChatGPT or Claude to Prefect Cloud

Local installation

Cloud deployment

Client setup

General setup

Credentials configuration

Default behavior

Environment variables

Credential precedence

Available capabilities

Read-only monitoring & inspection

Intelligent debugging

Documentation access

Mutations via CLI or SDK

Prompting tips

Use the prefect CLI for write operations

Leverage the docs proxy

Ask diagnostic questions

Learn more

​What is the Prefect MCP server?

​Security considerations

​Installation

​Connect ChatGPT or Claude to Prefect Cloud

​Local installation

​Cloud deployment

​Client setup

​General setup

​Credentials configuration

​Default behavior

​Environment variables

​Credential precedence

​Available capabilities

​Read-only monitoring & inspection

​Intelligent debugging

​Documentation access

​Mutations via CLI or SDK

​Prompting tips

​Use the prefect CLI for write operations

​Leverage the docs proxy

​Ask diagnostic questions

​Learn more

What is the Prefect MCP server?

Security considerations

Installation

Connect ChatGPT or Claude to Prefect Cloud

Local installation

Cloud deployment

Client setup

General setup

Credentials configuration

Default behavior

Environment variables

Credential precedence

Available capabilities

Read-only monitoring & inspection

Intelligent debugging

Documentation access

Mutations via CLI or SDK

Prompting tips

Use the prefect CLI for write operations

Leverage the docs proxy

Ask diagnostic questions

Learn more