About Sunra.ai Mcp Server
Sunra.ai Mcp Server connects MCP clients to Sunra.ai model inference services. It provides request management, model discovery and schema lookup, plus file upload over stdio or HTTP.
Key features
- 01Submit, track, retrieve, cancel, and await requests
- 02List and search available models
- 03Retrieve model endpoint schemas
- 04Upload files to Sunra.ai
- 05stdio and HTTP transports
- 06Configure API key
Use cases
- 01Submit a media-generation request to a model
- 02Check a request and retrieve its result
- 03Find models and inspect endpoint schemas
- 04Upload files for use with Sunra.ai
MCP support
It exposes Sunra.ai request, model-management, file-upload, and API-key tools to MCP clients, using stdio or HTTP transport.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
10Saved tool list · updated 3w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| endpointId | string | Yes | The ID of the API endpoint to submit to |
| input | any | No | The input data to send to the endpoint |
| webhookUrl | string | No | Optional webhook URL to receive completion notifications |
Details
From the project READMESunra MCP Server
A Model Context Protocol (MCP) server that provides tools for interacting with Sunra.ai services.
Installation
From npm (Recommended)
npx @sunra/mcp-server --help
Local Development
git clone https://github.com/sunra-ai/sunra-clients.git
cd sunra-clients/mcp-server
npm install
npm run build
Usage
Command Line Options
sunra-mcp-server [options]
Options:
-t, --transport <type> Transport type: 'stdio' or 'http' (default: stdio)
-p, --port <number> Port for HTTP transport (default: 3000)
-h, --host <string> Host for HTTP transport (default: localhost)
--help Show this help message
Examples:
sunra-mcp-server # Start with stdio transport
sunra-mcp-server --transport http # Start with HTTP transport on port 3000
sunra-mcp-server -t http -p 8080 # Start with HTTP transport on port 8080
For Cursor IDE
Add the following to your .cursor/mcp.json file:
{
"mcpServers": {
"sunra-mcp-server": {
"command": "npx",
"args": ["@sunra/mcp-server"],
"env": {
"SUNRA_KEY": "${SUNRA_KEY}"
}
}
}
}
For Claude Desktop
Add the following to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"sunra-mcp-server": {
"command": "npx",
"args": ["@sunra/mcp-server"],
"env": {
"SUNRA_KEY": "${SUNRA_KEY}"
}
}
}
}
Features
- Base Tools: Submit, status, result, cancel, subscribe operations
- Model Management: List, search, and get schema information for AI models
- File Management: Upload files to Sunra.ai
- Authentication: Secure API key management
- Multiple Transports: Supports both stdio (for Claude Desktop) and HTTP (for Cursor)
Tools
Base Operations
submit- Submit a request to a model endpointstatus- Check the status of a requestresult- Get the result of a completed requestcancel- Cancel a pending requestsubscribe- Submit and wait for completion
Model Management
list-models- List all available modelssearch-models- Search for models by name or descriptionmodel-schema- Get input and output schemas for a specific model endpoint
File Management
upload- Upload files to Sunra.ai storage
Authentication
set-sunra-key- Configure your Sunra.ai API key
Usage Examples
Model Schema Tool
The model-schema tool now accepts a model slug in the format owner/model/endpoint and returns only the input and output schemas:
# Get schema for a specific model endpoint
model-schema --modelSlug "black-forest-labs/flux-kontext-max/text-to-image"
Reference Resolution
The tool automatically resolves OpenAPI $ref references to provide fully expanded schemas. For example, if the original OpenAPI schema contains:
{
"schema": {
"$ref": "#/components/schemas/TextToVideoInput"
}
}
The tool will resolve this reference and return the actual schema definition:
{
"inputSchema": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "Text prompt for video generation"
},
"duration": {
"type": "integer",
"enum": [5, 10],
"description": "Duration of the video in seconds"
}
},
"required": ["prompt"]
}
}
The tool handles:
- ✅ Simple references (
#/components/schemas/SchemaName) - ✅ Nested references within objects and arrays
- ✅ Circular references (marked with
$circular: true) - ✅ Missing references (graceful fallback to original
$ref)
Response Format
Response format:
{
"success": true,
"modelSlug": "black-forest-labs/flux-kontext-max/text-to-image",
"owner": "black-forest-labs",
"model": "flux-kontext-max",
"endpoint": "text-to-image",
"inputSchema": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "Text prompt for image generation"
}
},
"required": ["prompt"]
},
"outputSchema": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Request ID"
},
"status": {
"type": "string",
"description": "Request status"
},
"output": {
"type": "object",
"description": "Generated output"
}
}
}
}
Development
Running Tests
npm test
Building
npm run build
Starting the Server
npm start
Configuration
Set your Sunra.ai API key as an environment variable:
export SUNRA_KEY="your-api-key-here"
Or use the set-sunra-key tool at runtime.
Publishing
To publish to npm:
npm run build
npm publish
API Reference
For detailed API documentation, see the Sunra.ai API documentation.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.