LLM Gateway
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Model Context Protocol (MCP)

Use LLM Gateway as an MCP server for Claude Code, Cursor, and other MCP-compatible clients

LLM Gateway provides a Model Context Protocol (MCP) server that enables AI assistants like Claude Code to access multiple LLM providers through a unified interface. This allows you to use any model from OpenAI, Anthropic, Google, and more directly from your AI coding assistant.

What is MCP?

The Model Context Protocol (MCP) is an open standard that allows AI assistants to connect with external tools and data sources. LLM Gateway's MCP server exposes tools for:

  • Chat completions - Send messages to any supported LLM
  • Image generation - Generate images using models like Qwen Image
  • Model discovery - List available models with capabilities and pricing

Available Tools

chat

Send a message to any LLM and get a response.

Parameters:

  • model (string) - The model to use (e.g., "gpt-4o", "claude-sonnet-4-20250514")
  • messages (array) - Array of messages with role and content
  • temperature (number, optional) - Sampling temperature (0-2)
  • max_tokens (number, optional) - Maximum tokens to generate

Example:

{
	"model": "gpt-4o",
	"messages": [{ "role": "user", "content": "Explain quantum computing" }],
	"temperature": 0.7
}

generate-image

Generate images from text prompts using AI image models.

Parameters:

  • prompt (string) - Text description of the image to generate
  • model (string, optional) - Image model (default: "qwen-image-plus")
  • size (string, optional) - Image size (default: "1024x1024")
  • n (number, optional) - Number of images (1-4, default: 1)

Example:

{
	"prompt": "A serene mountain landscape at sunset",
	"model": "qwen-image-max",
	"size": "1024x1024"
}

list-models

List available LLM models with capabilities and pricing.

Parameters:

  • include_deactivated (boolean, optional) - Include deactivated models
  • exclude_deprecated (boolean, optional) - Exclude deprecated models
  • limit (number, optional) - Maximum models to return (default: 20)
  • family (string, optional) - Filter by family (e.g., "openai", "anthropic")

list-image-models

List all available image generation models.

Example output:

# Image Generation Models

## Qwen Image Plus
- **Model ID:** `qwen-image-plus`
- **Description:** Text-to-image with excellent text rendering
- **Price:** $0.03 per request

## Qwen Image Max
- **Model ID:** `qwen-image-max`
- **Description:** Highest quality text-to-image
- **Price:** $0.075 per request

Setup

Get Your API Key

  1. Log in to your LLM Gateway dashboard
  2. Navigate to API Keys section
  3. Create a new API key and copy it

Configure Claude Code

Add the MCP server to your Claude Code configuration file (~/.claude/claude_desktop_config.json):

{
  "mcpServers": {
    "llmgateway": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-remote", "https://api.llmgateway.io/mcp"],
      "env": {
        "API_KEY": "your-api-key-here"
      }
    }
  }
}

Or use the HTTP transport directly:

{
  "mcpServers": {
    "llmgateway": {
      "url": "https://api.llmgateway.io/mcp",
      "headers": {
        "Authorization": "Bearer your-api-key-here"
      }
    }
  }
}

Restart Claude Code

Restart Claude Code to load the new MCP configuration. You should now see the LLM Gateway tools available.

Test the Integration

Try using the tools in Claude Code:

  • "Use the chat tool to ask GPT-4o about TypeScript best practices"
  • "Generate an image of a futuristic city using the generate-image tool"
  • "List all available models from Anthropic"

Cursor supports MCP servers through its settings. Configure the LLM Gateway MCP server:

  1. Open Cursor Settings
  2. Navigate to Features > MCP
  3. Add a new MCP server with:
    • URL: https://api.llmgateway.io/mcp
    • Headers: Authorization: Bearer your-api-key-here

MCP support in Cursor may require a specific version. Check Cursor's documentation for the latest compatibility information.

LLM Gateway's MCP server supports the standard HTTP Streamable transport. Configure your client with:

  • Endpoint: https://api.llmgateway.io/mcp
  • Authentication: Bearer token via Authorization header or x-api-key header
  • Protocol Version: 2024-11-05

Direct HTTP Example:

curl -X POST https://api.llmgateway.io/mcp \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/list"
  }'

Server-Sent Events (SSE):

For real-time updates, connect with Accept: text/event-stream:

curl -N https://api.llmgateway.io/mcp \
  -H "Accept: text/event-stream" \
  -H "Authorization: Bearer your-api-key"

Use Cases

Multi-Model Access in Claude Code

Use Claude Code to interact with models it doesn't natively support:

Use the chat tool with model "gpt-4o" to analyze this code for security issues.

Image Generation

Generate images directly from your AI assistant:

Use generate-image to create a logo for my new startup.
It should be minimalist, blue and white, representing AI and cloud computing.

Cost-Effective Model Selection

Query available models to find the best option for your task:

List models from OpenAI and Anthropic, then use the cheapest one for this simple task.

Authentication

The MCP server supports two authentication methods:

  1. Bearer Token - Authorization: Bearer your-api-key
  2. API Key Header - x-api-key: your-api-key

Your API key is the same one you use for the REST API and works across all LLM Gateway services.

OAuth Support

For applications that prefer OAuth authentication, LLM Gateway's MCP server implements OAuth 2.0:

  • Authorization Endpoint: /oauth/authorize
  • Token Endpoint: /oauth/token
  • Registration Endpoint: /oauth/register
  • Supported Flows: Authorization Code, Client Credentials

Troubleshooting

Connection Errors

If you're having trouble connecting:

  1. Verify your API key is valid
  2. Check the endpoint URL is correct: https://api.llmgateway.io/mcp
  3. Ensure your firewall allows outbound HTTPS connections

Tool Not Found

If tools aren't appearing:

  1. Restart your MCP client
  2. Check the configuration syntax
  3. Verify the MCP server is responding: GET https://api.llmgateway.io/mcp

Rate Limiting

The MCP server respects your account's rate limits. If you're hitting limits:

  1. Check your usage in the dashboard
  2. Consider upgrading your plan
  3. Implement request queuing in your application

Need help? Join our Discord community for support.

Benefits

  • Unified Access - Use 200+ models from 20+ providers through one interface
  • Cost Tracking - Monitor usage and costs in the LLM Gateway dashboard
  • Caching - Automatic response caching reduces costs and latency
  • Fallback - Automatic provider failover ensures reliability
  • Image Generation - Generate images directly from your AI assistant

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