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MCP Server Python logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 7:32:16 PM

MCP Server Python

User RatingsBe the first to rate and review this MCP server!
View Repository31 GitHub StarsTotal stargazers on GitHub for the source repository (31 stars).Visit Website
workfloworchestrationdockerkestrapython

MCP server implementing Kestra workflow orchestration API with configurable tools and auth, runnable via Docker.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON ▾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for kestra-io/mcp-server-python, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives☁️ More in Cloud Platforms

Overview

This MCP server provides integration with the Kestra workflow orchestration platform, exposing its API and tools to AI agents. It supports both open source and Enterprise Edition Kestra deployments with authentication via username/password or API token. The server can be run locally or in Docker, allowing configuration of enabled tools and logging levels. Use it when you want AI agents to interact with Kestra workflows, executions, logs, and related resources.

Use cases

•Manage and orchestrate workflows programmatically
•Query and control workflow executions
•Access and manipulate Kestra files and logs
•Enable AI agents to interact with Kestra namespaces and key-value stores
•Customize tool availability based on Kestra edition and user needs

Key features

•Supports Kestra OSS and Enterprise Edition APIs
•Dockerized deployment with environment variable configuration
•Configurable enabled/disabled tools including backfill, execution, flow, logs, and more
•Authentication via username/password or API token
•Adjustable logging levels (ERROR, WARNING, INFO, DEBUG)
•Supports multiple AI clients like Cursor, Claude, Windsurf, and VS Code

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Server Python.

Extracted Tool Capabilities
Supports Kestra OSS and Enterprise Edition APIs
Dockerized deployment with environment variable configuration
Configurable enabled/disabled tools including backfill, execution, flow, logs, and more
Authentication via username/password or API token
Adjustable logging levels (ERROR, WARNING, INFO, DEBUG)
Supports multiple AI clients like Cursor, Claude, Windsurf, and VS Code

Documentation Overview

Kestra Python MCP Server

You can run the MCP Server in a Docker container. This is useful if you want to avoid managing Python environments or dependencies on your local machine.

Using Kestra AI Agent

See kestra_mcp_docker.

Minimal configuration for OSS users

Paste the following configuration into your MCP settings (e.g., Cursor, Claude, or VS Code):

config.json
{
  "mcpServers": {
    "kestra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--pull",
        "always",
        "-e",
        "KESTRA_BASE_URL",
        "-e",
        "KESTRA_TENANT_ID",
        "-e",
        "KESTRA_MCP_DISABLED_TOOLS",
        "-e",
        "KESTRA_MCP_LOG_LEVEL",
        "-e",
        "KESTRA_USERNAME",
        "-e",
        "KESTRA_PASSWORD",
        "ghcr.io/kestra-io/mcp-server-python:latest"
      ],
      "env": {
        "KESTRA_BASE_URL": "http://host.docker.internal:8080/api/v1",
        "KESTRA_TENANT_ID": "main",
        "KESTRA_MCP_DISABLED_TOOLS": "ee",
        "KESTRA_MCP_LOG_LEVEL": "ERROR",
        "KESTRA_USERNAME": "admin@kestra.io",
        "KESTRA_PASSWORD": "your_password"
      }
    }
  }
}

Minimal configuration for EE users

config.json
{
  "mcpServers": {
    "kestra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--pull",
        "always",
        "-e", "KESTRA_BASE_URL",
        "-e", "KESTRA_API_TOKEN",
        "-e", "KESTRA_TENANT_ID",
        "-e", "KESTRA_MCP_LOG_LEVEL",
        "ghcr.io/kestra-io/mcp-server-python:latest"
      ],
      "env": {
        "KESTRA_BASE_URL": "http://host.docker.internal:8080/api/v1",
        "KESTRA_API_TOKEN": "<your_kestra_api_token>",
        "KESTRA_TENANT_ID": "main",
        "KESTRA_MCP_LOG_LEVEL": "ERROR"
      }
    }
  }
}

Detailed Configuration using Docker

config.json
{
  "mcpServers": {
    "kestra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--pull",
        "always",
        "-e", "KESTRA_BASE_URL",
        "-e", "KESTRA_API_TOKEN",
        "-e", "KESTRA_TENANT_ID",
        "-e", "KESTRA_USERNAME",
        "-e", "KESTRA_PASSWORD",
        "-e", "KESTRA_MCP_DISABLED_TOOLS",
        "-e", "KESTRA_MCP_LOG_LEVEL",
        "ghcr.io/kestra-io/mcp-server-python:latest"
      ],
      "env": {
        "KESTRA_BASE_URL": "http://host.docker.internal:8080/api/v1",
        "KESTRA_API_TOKEN": "<your_kestra_api_token>",
        "KESTRA_TENANT_ID": "main",
        "KESTRA_USERNAME": "admin",
        "KESTRA_PASSWORD": "admin",
        "KESTRA_MCP_DISABLED_TOOLS": "ee",
        "KESTRA_MCP_LOG_LEVEL": "ERROR"
      }
    }
  }
}

Notes:

  • Replace <your_kestra_api_token>, <your_google_api_key>, and <your_helicone_api_key> with your actual credentials.
  • For OSS installations, you can use KESTRA_USERNAME and KESTRA_PASSWORD instead of KESTRA_API_TOKEN.
  • To disable Enterprise Edition tools in OSS, set KESTRA_MCP_DISABLED_TOOLS=ee.
  • The host.docker.internal hostname allows the Docker container to access services running on your host machine (such as the Kestra API server on port 8080). This works on macOS and Windows. On Linux, you may need to use the host network mode or set up a custom bridge.
  • The -e flags pass environment variables from your MCP configuration into the Docker container.

Available Tools

  • 🔄 backfill
  • ⚙️ ee (Enterprise Edition tools)
  • ▶️ execution
  • 📁 files
  • 🔀 flow
  • 🗝️ kv
  • 📋 logs
  • 🌐 namespace
  • 🔁 replay
  • ♻️ restart
  • ⏸️ resume

Note: The ee tool group contains Enterprise Edition specific functionality and is only available in EE/Cloud editions. For OSS users, you can disable EE tools by adding KESTRA_MCP_DISABLED_TOOLS=ee to your .env file.

Optionally, you can include KESTRA_MCP_DISABLED_TOOLS in your .env file listing the tools that you prefer to disable. For example, if you want to disable Namespace Files tools, add this to your .env file:

dotenv
KESTRA_MCP_DISABLED_TOOLS=files

To disable multiple tools, separate them with comma:

dotenv
KESTRA_MCP_DISABLED_TOOLS=ee

Logging Configuration

By default, the MCP server only logs ERROR level messages to minimize noise. You can control the logging level using the KESTRA_MCP_LOG_LEVEL environment variable:

dotenv
# Only show ERROR messages (default)
KESTRA_MCP_LOG_LEVEL=ERROR

# Show WARNING and ERROR messages
KESTRA_MCP_LOG_LEVEL=WARNING

# Show INFO, WARNING, and ERROR messages
KESTRA_MCP_LOG_LEVEL=INFO

# Show all messages including DEBUG
KESTRA_MCP_LOG_LEVEL=DEBUG

When using Docker, add the environment variable to your MCP configuration:

config.json
{
  "mcpServers": {
    "kestra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--pull",
        "always",
        "-e", "KESTRA_BASE_URL",
        "-e", "KESTRA_MCP_LOG_LEVEL",
        "ghcr.io/kestra-io/mcp-server-python:latest"
      ],
      "env": {
        "KESTRA_BASE_URL": "http://host.docker.internal:8080/api/v1",
        "KESTRA_MCP_LOG_LEVEL": "ERROR"
      }
    }
  }
}

Local development

To run the MCP Server for Kestra locally (e.g. if you want to extend it with new tools), make sure to create a virtual environment first:

bash
uv venv --python 3.13
uv pip install -r requirements.txt

Create an .env file in the root directory of the project similar to the .env_example file. For OSS installations, you can use basic authentication with KESTRA_USERNAME and KESTRA_PASSWORD. For EE/Cloud installations, use KESTRA_API_TOKEN. To disable Enterprise Edition tools in OSS, add KESTRA_MCP_DISABLED_TOOLS=ee to your .env file.

Then, follow the instructions below explaining how to test your local server in Cursor, Windsurf, VS Code or Claude Desktop.


Usage in Cursor, Windsurf, VS Code or Claude Desktop

To use the Python MCP Server with Claude or modern IDEs, first check what is the path to uv on your machine:

bash
which uv

Copy the path returned by which uv and paste it into the command section. Then, replace the --directory by the path where you cloned the Kestra MCP Server repository. For example:

config.json
{
  "mcpServers": {
    "kestra": {
      "command": "/Users/annageller/.local/bin/uv",
      "args": [
        "--directory",
        "/Users/annageller/gh/mcp-server-python/src",
        "run",
        "server.py"
      ]
    }
  }
}

You can paste that in the Cursor MCP settings or Claud Developer settings.

VS Code setup

In your VS Code project directory, add a folder .vscode and within that folder, create a file called mcp.json. Paste your MCP configuration into that file (note that in VS Code, the key is servers instead of mcpServers):

config.json
{
  "servers": {
    "kestra": {
      "command": "/Users/annageller/.local/bin/uv",
      "args": [
        "--directory",
        "/Users/annageller/gh/mcp-server-python/src",
        "run",
        "server.py"
      ]
    }
  }
}

A small Start button should show up, click on it to start the server.

img.png

If you now navigate to the GitHub Copilot tab and switch to the Agent mode, you will be able to directly interact with the Kestra MCP Server tools. For example, try typing the prompt: "List all flows in the tutorial namespace".

img_1.png

If you click on continue, you will see the result of the command in the output window.

img_2.png

FAQ

Question: Do I have to manually start the server as an always-on process?

No, you don't have to run the server manually, as when using the stdio transport, the AI IDEs/chat-interfaces (Cursor, Windsurf, VS Code or Claude Desktop) launch the MCP server as a subprocess. This subprocess communicates with AI IDEs via JSON-RPC messages over standard input and output streams. The server receives messages through stdin and sends responses through stdout.

Question: Do I have to manually activate the virtual environment for the MCP Server?

No, because we use uv. Unlike traditional Python package managers, where virtual environment activation modifies shell variables like PATH, uv directly uses the Python interpreter and packages from the .venv directory without requiring environment variables to be set first. Just make sure you have created a uv virtual environment with uv venv and installed the required packages with uv pip install as described in the previous section.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
31
Stargazers on the source repository.
Last commit
4mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Server Python

For OSS Kestra, use KESTRA_USERNAME and KESTRA_PASSWORD environment variables; for Enterprise Edition, use KESTRA_API_TOKEN.

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Technical Specs & Signals

Category☁️Cloud Platforms
PricingBring your own API key (usage-based cost)
More technical detailsExpand ▾
AuthAPI key
ClientsCursor, Claude Desktop, Windsurf, Cline / VS Code
Last updatedAug 9, 2026
11/11 checks healthy over the last 32d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars31
GitHub Star CountTotal stargazers on GitHub representing community popularity (31 stars).
Last commit4mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on May 4, 2026
35Quality signal: Fair · 35/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools12/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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