> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/changelog/explore-by-month/april-2026/mcp-server.md).

# MCP Server

Roboflow MCP Server lets you connect AI assistants, like Claude Code and others, directly to your Roboflow workspace. The server provides access to 30 Roboflow tools for AI agents over streamable HTTP, authenticating securely with a standard Roboflow API key. This enables coding agents to better assist when building and deploying a vision application, from creating projects, uploading images, triggering model training, to running inference.

By delegating tasks to an AI agent via MCP Server, you can streamline development of your vision pipelines. For example, you can prompt an assistant to initiate auto-labeling jobs or build and validate sophisticated workflows in Roboflow. This enables you to to focus on visual validation and judging results while the agent handles API execution.

[Learn more about the MCP Server](https://mcp.roboflow.com/)

[See MCP Server documentation](https://docs.roboflow.com/developer/mcp-server) 


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.roboflow.com/changelog/explore-by-month/april-2026/mcp-server.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.