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MCP server · Developer Tools

Sunra AI

Search for and run AI models on [Sunra.ai](https://sunra.ai). Discover models, create video, image, and 3D model content, track their status, and manage the generated media.

Unclaimed Apache-2.0 last commit 11 months ago video-generationaisdkinference-apisunracontentimage-generation
50Fair

Scored 2 days ago · breakdown

About Sunra AI

Sunra AI is an MCP server published by sunra-ai in the Developer Tools category: search for and run AI models on [Sunra.ai](https://sunra.ai). Discover models, create video, image, and 3D model content, track their status, and manage the generated media. It has been installed 0 times through Conduid.

The repository has 7 stars and 0 forks, with the last commit 11 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx sunra-clients

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

@sunra/mcp-server@0.1.2@sunra/mcp-server@0.1.2
@sunra/mcp-server@0.0.3@sunra/mcp-server@0.0.3
@sunra/client@0.5.0@sunra/client@0.5.0
@sunra/client@0.3.8@sunra/client@0.3.8

README

sunra.ai Client Libraries

English | 简体中文

License PyPI - Version Maven Central Version Discord

About the Project

This repository contains the official client libraries for sunra.ai, a platform for deploying and running AI models. The libraries provide robust and user-friendly interfaces for integrating sunra.ai endpoints into your applications across multiple programming languages.

Available Client Libraries

🐍 Python Client

  • Location: clients/python/
  • Package: sunra-client (PyPI)
  • Features: Synchronous and asynchronous support, streaming responses, file uploads
  • Installation: pip install sunra-client

📦 JavaScript/TypeScript Client

  • Location: clients/javascript/
  • Package: @sunra/client (npm)
  • Features: Works in Web, Node.js, and React Native environments
  • Installation: npm install @sunra/client

☕ Java Client

  • Location: clients/java/
  • Package: ai.sunra.client:sunra-client (Maven Central)
  • Features: Synchronous, asynchronous, and Kotlin coroutine support
  • Installation: implementation "ai.sunra.client:sunra-client:0.1.6"

Quick Start

Before using any client library, you'll need to:

  1. Sign up at sunra.ai
  2. Get your API key from the dashboard
  3. Set your API key as an environment variable: export SUNRA_KEY=your-api-key

Python Example

import sunra_client

# Simple synchronous call
result = sunra_client.subscribe(
    "black-forest-labs/flux-kontext-pro/text-to-image",
    arguments={"prompt": "a cute cat, realistic, orange"}
)
print(result["images"][0]["url"])

# Asynchronous call
async def main():
    result = await sunra_client.subscribe_async(
        "black-forest-labs/flux-kontext-pro/text-to-image",
        arguments={"prompt": "a cute cat, realistic, orange"}
    )
    print(result["images"][0]["url"])

JavaScript Example

import { createSunraClient } from "@sunra/client";

const sunra = createSunraClient({
  credentials: process.env.SUNRA_KEY,
});

const result = await sunra.subscribe(
  "black-forest-labs/flux-kontext-pro/text-to-image",
  {
    input: {
      prompt: "a cute cat, realistic, orange"
    }
  }
);
console.log(result.images[0].url);

Java Example

import ai.sunra.client.*;

var sunra = SunraClient.withEnvCredentials();

var result = sunra.subscribe(
    "black-forest-labs/flux-kontext-pro/text-to-image",
    SubscribeOptions.<JsonObject>builder()
        .input(Map.of("prompt", "a cute cat, realistic, orange"))
        .resultType(JsonObject.class)
        .build()
);
System.out.println(result.getData());

Server Proxy

For client-side applications, we provide a server proxy to securely handle API calls without exposing your credentials. Available for popular frameworks:

  • Location: server-proxy/
  • Package: @sunra/server-proxy (npm)
  • Supports: Next.js, Express, Hono, Remix, SvelteKit

MCP Server (Model Context Protocol)

The MCP server provides a universal interface for AI model tools, enabling seamless integration with modern code assistants and IDEs such as Cursor and Claude Desktop. It acts as a bridge between Sunra.ai and your development environment, exposing Sunra's models and tools via the Model Context Protocol.

Why use the MCP server?

  • Enables code assistants (like Cursor, Claude, etc.) to access Sunra models and tools directly from your editor
  • Supports listing models, fetching schemas, submitting jobs, streaming results, and more
  • Secure: API keys are managed via environment variables or runtime configuration
  • No need to write glue code—just run the server and connect your tool

Quick Start

1. Install & Run (no local build needed)

npx @sunra/mcp-server --transport http --port 3925

2. For Cursor IDE

  • Add to your .cursor/mcp.json:
{
  "mcpServers": {
    "sunra-mcp-server": {
      "url": "http://localhost:3925/sse"
    }
  }
}
  • Set your API key:
    export SUNRA_KEY="your-api-key-here"
    
  • In Cursor, select the sunra-mcp-server and use tools like list-models, model-schema, etc.

3. For Claude Desktop (Anthropic)

  • Start the server in stdio mode (default):
    npx @sunra/mcp-server
    
  • In Claude Desktop settings, add a new MCP server:
    • Type: Local executable
    • Command: npx @sunra/mcp-server
    • Environment Variables:
      SUNRA_KEY=your-api-key-here
      
  • In Claude, select the sunra-mcp-server and use the available tools.

4. Advanced Usage & Documentation

Examples

The repository includes comprehensive examples for different frameworks and use cases:

Development

To set up the development environment:

  1. Clone the repository
  2. Install dependencies: pnpm i -r
  3. Set up your API key: export SUNRA_KEY=your-api-key
  4. Run examples or tests as needed

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Make sure you read our Code of Conduct
  2. Fork the project and clone your fork
  3. Setup the local environment with npm install
  4. Create a feature branch (git checkout -b feat/add-cool-thing) or a bugfix branch (git checkout -b fix/smash-that-bug)
  5. Commit the changes (git commit -m 'feat(client): added a cool thing') - use conventional commits
  6. Push to the branch (git push --set-upstream origin feat/add-cool-thing)
  7. Open a Pull Request

Check the good first issue queue, your contribution will be welcome!

License

Distributed under the Apache 2.0 License. See LICENSE for more information.

Credits

This project is derived from:

and adapted to work with sunra.ai. The original projects are licensed under the MIT/Apache 2.0 License. We extend our gratitude to the original authors for their contributions.

README mirrored from the source repository 2 days ago. The original is authoritative.

Questions

About Sunra AI

How do I install Sunra AI?

Run npx sunra-clients, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Sunra AI safe to use with an AI agent?

Its trust score is 50 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Sunra AI still maintained?

The last commit was 11 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.