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runapi-ai
by runapi-ai
README.md
<h1 align="center">RunAPI GPT Image MCP Server</h1>

<p align="center">
  <strong>GPT Image API access for AI agents: run image generation operations, poll asynchronous results, and check pricing through one focused MCP server.</strong>
</p>

<p align="center">
  <sub>Works with Claude Code, Codex, Cursor, Windsurf, VS Code, Roo Code, and any MCP-compatible host.</sub>
</p>

<p align="center">
  <a href="https://www.npmjs.com/package/@runapi.ai/gpt-image-mcp"><img src="https://img.shields.io/npm/v/%40runapi.ai/gpt-image-mcp?style=flat-square&color=blue" alt="npm version"></a>
  <a href="https://github.com/runapi-ai/gpt-image-mcp"><img src="https://img.shields.io/badge/GitHub-runapi--ai%2Fgpt--image--mcp-24292f?style=flat-square" alt="GitHub repository"></a>
  <a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue?style=flat-square" alt="Apache-2.0 license"></a>
  <img src="https://img.shields.io/badge/Type-MCP_Server-blue?style=flat-square" alt="MCP Server">
  <img src="https://img.shields.io/badge/Models-1-16a34a?style=flat-square" alt="1 models">
</p>

<p align="center">
  <a href="#install">Install</a> |
  <a href="#tools">Tools</a> |
  <a href="#models">Models</a> |
  <a href="#agent-prompts">Agent Prompts</a> |
  <a href="#configuration">Configuration</a> |
  <a href="#links">Links</a>
</p>

---

## Why This Package?

`@runapi.ai/gpt-image-mcp` is a focused Model Context Protocol server for the **GPT Image** model line on RunAPI.
It gives MCP-compatible assistants direct access to 2 endpoints and 1 model variant without loading the full RunAPI catalog.

Use this per-model server when an agent should stay scoped to GPT Image. Use [`@runapi.ai/mcp`](https://github.com/runapi-ai/mcp) when one assistant should discover every RunAPI model line.

---

## Install

Add it to Claude Code:

```bash
claude mcp add gpt-image -s user -- npx -y @runapi.ai/gpt-image-mcp
```

Use project scope when the server should be shared with a repository:

```bash
claude mcp add gpt-image -s project -- npx -y @runapi.ai/gpt-image-mcp
```

Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:

```json
{
  "mcpServers": {
    "gpt-image": {
      "command": "npx",
      "args": ["-y", "@runapi.ai/gpt-image-mcp"]
    }
  }
}
```

`check_pricing` works before sign-in. For task creation and status polling, ask your assistant to call the `login` tool. It opens a browser login and saves credentials to `~/.config/runapi/config.json`, the same file used by `runapi login`.
Headless and CI hosts can still set `RUNAPI_API_KEY` before starting the MCP host.

Ready-made examples are in [`examples/`](examples/) for Claude, Cursor, Windsurf, VS Code, and Roo Code.

---

## Tools

| Tool | Auth | Purpose |
|---|---|---|
| `edit_image` | Yes | Create a GPT Image edit image task and optionally wait for a terminal status. Returns the task id, status, and output URLs. |
| `text_to_image` | Yes | Create a GPT Image text to image task and optionally wait for a terminal status. Returns the task id, status, and output URLs. |
| `get_task` | Yes | Fetch the current status and latest payload for an existing task. |
| `check_pricing` | No | Look up current pricing for a GPT Image model and endpoint. |

---

## Models

GPT Image covers 1 model variant across 2 endpoints. Each tool accepts the models listed for it:

| Tool | Models |
|---|---|
| `edit_image` | `gpt-image-1.5` |
| `text_to_image` | `gpt-image-1.5` |

Model availability can change between releases. Use `check_pricing` or the [GPT Image model page](https://runapi.ai/models/gpt-image) for the current catalog view.

---

## Agent Prompts

Ask your assistant in natural language; it can inspect pricing, create the task, and return the task id plus output URLs.

### Create a task

```text
Run a GPT Image edit image task with RunAPI.
```

The assistant can call `check_pricing`, then `edit_image`, and return the task id, status, and output URLs.

### Submit without waiting

```text
Create the task but don't wait for it to finish.
```

The assistant calls the create tool with `wait: false` and returns the task id. Check on it later with `get_task`.

### Check pricing before creating

```text
Check current GPT Image pricing, then create the task if it matches my request.
```

The assistant calls `check_pricing` and can link to the [GPT Image model page](https://runapi.ai/models/gpt-image) for the canonical catalog entry.

---

## Configuration

The server resolves auth in this order:

1. `RUNAPI_API_KEY` environment variable, useful for headless and CI hosts
2. `~/.config/runapi/config.json`, created by the MCP `login` tool or `runapi login`
3. No key, which still allows `check_pricing`

The config file is normally managed by login. A pre-provisioned headless config can use:

```json
{
  "apiKey": "your_runapi_key"
}
```

Do not commit real API keys.

---

## Links

| Resource | URL |
|---|---|
| GPT Image model page | [https://runapi.ai/models/gpt-image](https://runapi.ai/models/gpt-image) |
| npm package | [@runapi.ai/gpt-image-mcp](https://www.npmjs.com/package/@runapi.ai/gpt-image-mcp) |
| GitHub repository | [runapi-ai/gpt-image-mcp](https://github.com/runapi-ai/gpt-image-mcp) |
| RunAPI MCP overview | [runapi.ai/mcp](https://runapi.ai/mcp) |
| RunAPI docs | [runapi.ai/docs](https://runapi.ai/docs) |

---

## License

Licensed under the [Apache License, Version 2.0](LICENSE).

TDQS

B3.4/5.0

Scored across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: authentication, two image generation modes, task status retrieval, and pricing lookup. The two generation tools are differentiated by input type (edit vs. text-to-image) with explicit descriptions.

Naming Consistency4/5

Most tools follow a verb_noun snake_case pattern (edit_image, get_task, check_pricing). 'login' and 'text_to_image' are minor deviations but remain intuitive and consistent in style.

Tool Count5/5

Five tools is well-scoped for an image generation server: authentication, two creation modes, task polling, and pricing. Each tool earns its place without redundancy or bloat.

Completeness4/5

The core create-and-retrieve workflow is well covered, including auth and pricing. Minor gaps exist such as no task cancellation, listing, or webhook support, but these are not essential for basic image generation usage.

Maintenance

ActivitySlowing
ResponsivenessNo issues