Roboflow MCP Server

# Roboflow MCP Server > A hosted Model Context Protocol (MCP) server that exposes Roboflow's computer vision platform — projects, datasets, images, annotations, versions, models, and Workflows — as tools for AI assistants. This server speaks MCP over streamable HTTP at `https://mcp.roboflow.com/mcp`. Clients can connect via an MCP URL only and will be prompted to sign in to Roboflow. ## Connection - [MCP endpoint](https://mcp.roboflow.com/mcp): streamable-http transport, supports MCP OAuth discovery - [OAuth protected-resource metadata](https://mcp.roboflow.com/.well-known/oauth-protected-resource/mcp) - [Homepage](https://mcp.roboflow.com/): install snippets for Claude Code, Claude Desktop, and other MCP clients ## Tool categories - **Agent** — chat with the Roboflow AI agent for Roboflow Q&A, advanced Workflow building, and CV solution planning - `agent_chat`: Chat with the Roboflow AI agent. - `agent_chat_result`: Collect the result of an agent_chat run that was still working. - `agent_conversations_list`: List Roboflow agent conversations in the workspace. - `agent_conversation_get`: Get a single agent conversation with its message history. - `agent_workflow_publish`: Publish the latest agent-edited draft of a workflow. - **Projects** — manage projects in your workspace - `projects_list`: List projects in the workspace associated with the credential. - `projects_create`: Create a new computer vision project. - `projects_health`: Get dataset health check for a project. - `projects_get`: Get detailed info about a project including versions, classes, splits, and trained models. - `projects_fork`: Enqueue an async fork of a public Universe project into your workspace. - **Project Deployment** — launch and manage a stable live endpoint for a project - `project_deployment_get`: Get the stable live endpoint state for a project. - `project_deployment_launch`: Create or prepare a stable Project Deployment. - `project_deployment_set