# VLM Run MCP

Vendor: VLM Run  
Category: docs  
Auth: API_KEY  
Composio slug: `vlm_run`

VLM Run provides multimodal agents, structured extraction, predictions, files, skills, feedback, and evaluation APIs.

## Tools

- **Create Skill** — Create a reusable skill from exactly one uploaded zip, prompt, or chat session.
- **Discover Extraction Schemas** — List supported structured-extraction domains, or return the full JSON schema for one domain when domain is provided.
- **Execute Agent** — Start a VLM Run agent execution from an existing agent name or inline configuration over multimodal inputs. Execution may consume credits and is asynchronous by default; poll the returned ID with VLM_RUN_GET_RUN.
- **Extract Structured JSON** — Start structured JSON extraction from images, a document, a video, or audio using a domain, custom schema, or skill. Extraction may consume credits; document, video, and audio runs are asynchronous by default, so poll the returned predictio
- **Find Files** — List uploaded files or find one by file ID or MD5 hash. In list mode, use offset and limit until has_more is false.
- **Find Skills** — List VLM Run skills or find one exact skill by ID, name, and optional version. In list mode, continue from next_offset while has_more is true.
- **Get Run** — Get the current status and result of one structured-extraction prediction or agent execution; call repeatedly to poll asynchronous work.
- **List Agents** — Return agents available to the connected account for selection before execution.
- **List Artifacts** — List artifact metadata belonging to exactly one chat session or agent execution. Use offset and limit to traverse pages until has_more is false.
- **List Runs** — List structured-extraction predictions or agent executions for the connected account. Use offset and limit to traverse pages until has_more is false.
- **Upload File** — Upload a local file to VLM Run for extraction, agent input, or skill creation. Retain the returned file ID for tools that consume uploaded files.

## Setup

1. Create or open a Switchy Project.
2. Open Integrations and connect VLM Run.
3. Authorise through api_key.
4. Teammates can now @-mention VLM Run tools in chat.

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Last verified: 2026-09-03T02:00:04.194Z  
Canonical URL: https://switchy.build/directory/mcps/vlm-run