Topaz MCP Server
<h1 align="center">RunAPI Topaz MCP Server</h1>
<p align="center">
<strong>Topaz API access for AI agents: run image and video 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/topaz-mcp"><img src="https://img.shields.io/npm/v/%40runapi.ai/topaz-mcp?style=flat-square&color=blue" alt="npm version"></a>
<a href="https://github.com/runapi-ai/topaz-mcp"><img src="https://img.shields.io/badge/GitHub-runapi--ai%2Ftopaz--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-2-16a34a?style=flat-square" alt="2 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/topaz-mcp` is a focused Model Context Protocol server for the **Topaz** model line on RunAPI.
It gives MCP-compatible assistants direct access to 2 endpoints and 2 model variants without loading the full RunAPI catalog.
Use this per-model server when an agent should stay scoped to Topaz. 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 topaz -s user -- npx -y @runapi.ai/topaz-mcp
```
Use project scope when the server should be shared with a repository:
```bash
claude mcp add topaz -s project -- npx -y @runapi.ai/topaz-mcp
```
Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:
```json
{
"mcpServers": {
"topaz": {
"command": "npx",
"args": ["-y", "@runapi.ai/topaz-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 |
|---|---|---|
| `upscale_image` | Yes | Create a Topaz upscale image task and optionally wait for a terminal status. Returns the task id, status, and output URLs. |
| `upscale_video` | Yes | Create a Topaz upscale video 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 Topaz model and endpoint. |
---
## Models
Topaz covers 2 model variants across 2 endpoints. Each tool accepts the models listed for it:
| Tool | Models |
|---|---|
| `upscale_image` | `topaz-upscale-image` |
| `upscale_video` | `topaz-upscale-video` |
Model availability can change between releases. Use `check_pricing` or the [Topaz model page](https://runapi.ai/models/topaz) 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 Topaz upscale image task with RunAPI.
```
The assistant can call `check_pricing`, then `upscale_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 Topaz pricing, then create the task if it matches my request.
```
The assistant calls `check_pricing` and can link to the [Topaz model page](https://runapi.ai/models/topaz) 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 |
|---|---|
| Topaz model page | [https://runapi.ai/models/topaz](https://runapi.ai/models/topaz) |
| npm package | [@runapi.ai/topaz-mcp](https://www.npmjs.com/package/@runapi.ai/topaz-mcp) |
| GitHub repository | [runapi-ai/topaz-mcp](https://github.com/runapi-ai/topaz-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
Scored across 5 tools
Each tool targets a clearly distinct action: upscale_image and upscale_video split by media type, get_task polls status, check_pricing handles billing lookup, and login handles auth. No two tools could reasonably be confused for one another.
Four of five tools follow a clean verb_noun pattern (upscale_image, upscale_video, get_task, check_pricing). Only 'login' deviates as a bare verb, which is a minor but forgivable inconsistency.
Five tools is well-scoped for a focused image/video upscaling service: two task-creation tools, one status poller, one pricing lookup, and one auth tool. Nothing feels padded or missing at the count level.
The core lifecycle (auth, create upscale task, poll status, check pricing) is covered, and results come back as output URLs. However, there is no cancel/delete task, no list-tasks, and no explicit result-download tool, leaving minor gaps an agent must work around.