# Roboflow MCP Server

> Use this tool when you need to streamline computer vision workflows by integrating dataset management, model training, and inference capabilities. It solves problems related to dataset searching, image uploading, and model evaluation, allowing for efficient management of computer vision projects. The tool takes natural language commands as input and outputs managed datasets, trained models, and inference results, making it ideal for use cases that require automated computer vision workflows.

Canonical page: https://skillsregistry.net/skills/nickedridge-wq-roboflow-mcp  
JSON: https://api.skillsregistry.net/v1/skills/nickedridge-wq-roboflow-mcp

## Description

Integrates the Roboflow platform with Claude Code to manage computer vision datasets, trigger training runs, and perform inference directly from the CLI. It enables users to search Roboflow Universe for public datasets and handle image uploads or model evaluations using natural language commands.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/nxoujsaz6e)
- **Repository:** <https://github.com/nickedridge-wq/roboflow-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "nickedridge-wq-roboflow-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nickedridge-wq-roboflow-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nickedridge-wq-roboflow-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt