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"
}
}
}
}