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Roboflow

@Erik

Create, train, and deploy computer vision models.
Overview

Roboflow MCP Server

This is a Model Context Protocol server that exposes Roboflow's computer vision platform as tools for AI assistants. It speaks MCP over streamable HTTP at /mcp and authenticates with a Roboflow API key sent in the x-api-key header.

Claude Code (CLI)

claude mcp add roboflow \
  --transport http https://mcp.roboflow.com/mcp \
  --header "x-api-key: YOUR_ROBOFLOW_API_KEY" \
  --header "Accept: application/json, text/event-stream"

Claude Desktop / Generic MCP Client

Add to your config (e.g. claude_desktop_config.json):

{
  "mcpServers": {
    "roboflow": {
      "type": "http",
      "url": "https://mcp.roboflow.com/mcp",
      "headers": {
        "x-api-key": "YOUR_ROBOFLOW_API_KEY",
        "Accept": "application/json, text/event-stream"
      }
    }
  }
}

Get your API key at https://app.roboflow.com/settings/api.

What this server provides

30 tools across these categories:

  • Projects — manage projects in your workspace
    projects_list, projects_create, projects_get
  • Images — prepare image uploads for a project
    images_prepare_upload, images_prepare_upload_zip, images_upload_zip_status, images_search
  • Annotations — save annotations to a project image
    annotations_save
  • Batch — organize images into batches and create labeling jobs
    annotation_batches_list, annotation_batches_get, annotation_jobs_create
  • Versions — create and inspect dataset versions
    versions_generate, versions_get, versions_export
  • Models — train models and monitor training progress
    models_list, models_get, models_infer, models_train, models_get_training_status
  • Workflows — build and execute inference pipelines
    workflows_list, workflows_get, workflows_create, workflows_update, workflow_blocks_list, workflow_blocks_get_schema, workflow_specs_validate, workflows_run, workflow_specs_run
  • Universe — search public datasets on Roboflow Universe
    universe_search
  • Meta — report issues or suggestions
    meta_feedback_send

Skills (expert knowledge as MCP resources)

Connected clients can read these as MCP resources for guidance on common tasks:

  • No skills registered.

For AI agents

A short, LLM-friendly summary of this server lives at /llms.txt following the llms.txt convention.

Server Config

{
  "mcpServers": {
    "roboflow": {
      "type": "http",
      "url": "https://mcp.roboflow.com/mcp",
      "headers": {
        "x-api-key": "YOUR_ROBOFLOW_API_KEY",
        "Accept": "application/json, text/event-stream"
      }
    }
  }
}
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