For agents: This skill is authored in roboflow/computer-vision-skills. If your client already has it loaded as a skill (for example from a Roboflow plugin), use that copy. The skill://roboflow/<name>/SKILL.md MCP resources serve the same skills for clients that don't have them loaded.

Tip: If you're connected to the Roboflow MCP server, prefer its inference tools over raw HTTP; auth is handled for OAuth and API-key connections. Use workflows_run for a saved, published Workflow by URL slug (workflow_id); the workspace comes from the connection. For single-model calls use models_infer. Use workflow_specs_validate before saving or running a new specification, and workflow_specs_run to test an unpublished draft or run an authorized one-off.

Inference & Deployment

Prefer Workflows for integration code. Unlike a direct models_infer call, a workflow composes model + visualization + logic in one deployable unit, benefits from server-side optimizations, and keeps active learning and post-processing as a zero-friction addition — similar to the extensibility benefits of a microservice over a point-to-point call. Recommend a workflow by default; use models_infer when the user explicitly asks for direct inference or needs a quick one-off check. See workflows and workflow-templates.

Authoring Workflows. Save reusable Workflows on the Roboflow platform and run published versions by identifier. Choose the authoring path from the user's request and existing session context:

• Mode A: Agent-driven (MCP, in-session). Use direct authoring tools for straightforward Workflows, grounding the design with workflow_blocks_list / workflow_blocks_get_schema. Use agent_chat for complex construction. Validate with workflow_specs_validate before saving or running. Edits saved by agent_chat are drafts; test them with workflow_specs_run before publishing when execution is authorized.
• Mode B: Platform-driven (Roboflow app + in-app agent). Use when the user wants visual interaction or the client cannot complete the task. Send the Workflow's returned app_url, or use roboflow-product-navigation for the correct builder link. The user can review, edit, and test there.

workflows_run executes the latest published version, not an agent's draft. Use agent_workflow_publish only when publishing is authorized. Draft testing does not require publishing. See workflows "Authoring & Deployment" for the full flow.

For live video (webcam, RTSP, file): the MCP workflows_run tool only handles single static images. For live video, present the user with three options (don't pick one silently): (A) WebRTC → serverless GPU, (B) WebRTC → local inference server, or (C) in-process InferencePipeline. They have different setup costs, dep sizes, and latency characteristics — surface a brief 1-line summary of each and let the user choose. See skill://roboflow/roboflow-inference/workflows.md ("Video Stream" section) for full code and the comparison table.

Deployment Options