Accelerate Orchestration with Kestra AI Tools

For the complete documentation index, see llms.txt. For a full content snapshot, see llms-full.txt. Append .md to any kestra.io/docs/* URL for plain Markdown.

Create, refine, and orchestrate workflows using natural language or autonomous decision-making.

Learn how Kestra AI tools accelerate orchestration

Kestra provides built-in AI features and external integrations that work at every layer of your workflow development:

  • Kestra MCP resources: connect any MCP-compatible AI tool (Claude Code, Cursor, etc.) to live Kestra plugin docs, blueprints, and documentation search — the fastest way to get accurate Kestra context in your AI coding agent.
  • AI Copilot: generate and refine flows from natural language inside the Kestra UI.
  • AI Agents: autonomous orchestration where tasks are chosen dynamically at runtime rather than following a fixed sequence.
  • Agent Skills: structured knowledge files that give AI coding agents the expertise to generate valid Kestra flows and operate environments via kestractl.

Kestra MCP resources

The Kestra MCP resources endpoint connects any MCP-compatible AI tool — Claude Code, Cursor, and others — to live Kestra plugin documentation, blueprints, and product docs. Instead of relying on training data, your AI agent queries it at runtime for current, accurate information about task properties, configuration options, and usage patterns.

AI Copilot

AI Copilot allows users to generate and refine flow definitions from natural language prompts. Instead of manually writing YAML, you can describe the desired behavior (for example, ”Make a REST API call to https://kestra.io/api/mock and allow failure”) and Copilot will generate the corresponding flow code. The generated YAML can then be reviewed, accepted, or modified. Copilot can also update existing flows incrementally, such as adding tasks or adjusting triggers, without affecting unrelated parts of the flow.

AI Agents

AI Agents provide autonomous orchestration capabilities. An AI Agent task uses a large language model (LLM), optional memory, and configured tools such as web search, task execution, or flow calling. The agent can dynamically decide which actions to take, loop until conditions are satisfied, and adapt based on new information. Unlike static flows that follow a fixed sequence, agents operate adaptively while remaining observable and fully defined as code.

Agent Skills

Agent Skills are structured knowledge files that teach external AI coding agents — such as Claude Code, Cursor, and Windsurf — how to generate Kestra flows and operate Kestra environments using kestractl. Unlike AI Copilot (which works inside the Kestra UI) or AI Agents (which run inside flows), Agent Skills bring Kestra expertise directly to your editor or terminal.

Summary

Together, these approaches offer complementary ways to work with AI:

  • Kestra MCP resources: gives external AI coding agents live access to Kestra plugin docs, blueprints, and documentation — no training data required.
  • AI Copilot: speeds up flow creation and modification by translating natural language instructions into YAML.
  • AI Agents: enable adaptive orchestration patterns where task sequences are not predetermined but are chosen dynamically at runtime.
  • Agent Skills: give external AI coding agents structured knowledge to generate valid Kestra flows and operate environments from your development tools.

AI Copilot and AI Agents are built into Kestra, while Kestra MCP resources and Agent Skills extend Kestra expertise to the external tools you already use.

Was this page helpful?