What is Outsource Mcp

Outsource-mcp is an MCP (Model Context Protocol) server that allows AI applications to delegate tasks to over 20 different model providers through a unified interface.

Use cases

Use cases include generating text for articles, creating images for marketing materials, and developing AI applications that require diverse model capabilities.

How to use

To use outsource-mcp, configure your MCP client with the provided JSON configuration, ensuring to include the necessary API keys for the model providers you intend to use.

Key features

Key features include multi-provider support for accessing over 20 AI providers, text and image generation capabilities, a simple API with three parameters (provider, model, prompt), and flexible authentication for only the providers you use.

Where to use

Outsource-mcp can be used in various fields such as AI development, content creation, image generation, and any application that requires integration with multiple AI models.

Outsource MCP

An MCP (Model Context Protocol) server that enables AI applications to outsource tasks to various model providers through a unified interface.

Compatible with any AI tool that supports the Model Context Protocol, including Claude Desktop, Cline, and other MCP-enabled applications.
Built with FastMCP for the MCP server implementation and Agno for AI agent capabilities.

Features

• 🤖 Multi-Provider Support: Access 20+ AI providers through a single interface
• 📝 Text Generation: Generate text using models from OpenAI, Anthropic, Google, and more
• 🎨 Image Generation: Create images using DALL-E 3 and DALL-E 2
• 🔧 Simple API: Consistent interface with just three parameters: provider, model, and prompt
• 🔑 Flexible Authentication: Only configure API keys for the providers you use

Configuration

Add the following configuration to your MCP client. Consult your MCP client’s documentation for specific configuration details.

{
  "mcpServers": {
    "outsource-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/gwbischof/outsource-mcp.git",
        "outsource-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-openai-key",
        "ANTHROPIC_API_KEY": "your-anthropic-key",
        "GOOGLE_API_KEY": "your-google-key",
        "GROQ_API_KEY": "your-groq-key",
        "DEEPSEEK_API_KEY": "your-deepseek-key",
        "XAI_API_KEY": "your-xai-key",
        "PERPLEXITY_API_KEY": "your-perplexity-key",
        "COHERE_API_KEY": "your-cohere-key",
        "FIREWORKS_API_KEY": "your-fireworks-key",
        "HUGGINGFACE_API_KEY": "your-huggingface-key",
        "MISTRAL_API_KEY": "your-mistral-key",
        "NVIDIA_API_KEY": "your-nvidia-key",
        "OLLAMA_HOST": "http://localhost:11434",
        "OPENROUTER_API_KEY": "your-openrouter-key",
        "TOGETHER_API_KEY": "your-together-key",
        "CEREBRAS_API_KEY": "your-cerebras-key",
        "DEEPINFRA_API_KEY": "your-deepinfra-key",
        "SAMBANOVA_API_KEY": "your-sambanova-key"
      }
    }
  }
}

Note: The environment variables are optional. Only include the API keys for the providers you want to use.

Quick Start

Once installed and configured, you can use the tools in your MCP client:

1. Generate text: Use the outsource_text tool with provider “openai”, model “gpt-4o-mini”, and prompt “Write a haiku about coding”
2. Generate images: Use the outsource_image tool with provider “openai”, model “dall-e-3”, and prompt “A futuristic city skyline at sunset”

Tools

outsource_text

Creates an Agno agent with a specified provider and model to generate text responses.

Arguments:

• provider: The provider name (e.g., “openai”, “anthropic”, “google”, “groq”, etc.)
• model: The model name (e.g., “gpt-4o”, “claude-3-5-sonnet-20241022”, “gemini-2.0-flash-exp”)
• prompt: The text prompt to send to the model

outsource_image

Generates images using AI models.

Arguments:

• provider: The provider name (currently only “openai” is supported)
• model: The model name (“dall-e-3” or “dall-e-2”)
• prompt: The image generation prompt

Returns the URL of the generated image.

Note: Image generation is currently only supported by OpenAI models (DALL-E 2 and DALL-E 3). Other providers only support text generation.

Supported Providers

The following providers are supported. Use the provider name (in parentheses) as the provider argument:

Core Providers

• OpenAI (openai) - GPT-4, GPT-3.5, DALL-E, etc. | Models
• Anthropic (anthropic) - Claude 3.5, Claude 3, etc. | Models
• Google (google) - Gemini Pro, Gemini Flash, etc. | Models
• Groq (groq) - Llama 3, Mixtral, etc. | Models
• DeepSeek (deepseek) - DeepSeek Chat & Coder | Models
• xAI (xai) - Grok models | Models
• Perplexity (perplexity) - Sonar models | Models

Additional Providers

• Cohere (cohere) - Command models | Models
• Mistral AI (mistral) - Mistral Large, Medium, Small | Models
• NVIDIA (nvidia) - Various models | Models
• HuggingFace (huggingface) - Open source models | Models
• Ollama (ollama) - Local models | Models
• Fireworks AI (fireworks) - Fast inference | Models
• OpenRouter (openrouter) - Multi-provider access | Models
• Together AI (together) - Open source models | Models
• Cerebras (cerebras) - Fast inference | Models
• DeepInfra (deepinfra) - Optimized models | Models
• SambaNova (sambanova) - Enterprise models | Models

Enterprise Providers

• AWS Bedrock (aws or bedrock) - AWS-hosted models | Models
• Azure AI (azure) - Azure-hosted models | Models
• IBM WatsonX (ibm or watsonx) - IBM models | Models
• LiteLLM (litellm) - Universal interface | Models
• Vercel v0 (vercel or v0) - Vercel AI | Models
• Meta Llama (meta) - Direct Meta access | Models

Environment Variables

Each provider requires its corresponding API key:

Provider	Environment Variable	Example
OpenAI	OPENAI_API_KEY	sk-…
Anthropic	ANTHROPIC_API_KEY	sk-ant-…
Google	GOOGLE_API_KEY	AIza…
Groq	GROQ_API_KEY	gsk_…
DeepSeek	DEEPSEEK_API_KEY	sk-…
xAI	XAI_API_KEY	xai-…
Perplexity	PERPLEXITY_API_KEY	pplx-…
Cohere	COHERE_API_KEY	…
Fireworks	FIREWORKS_API_KEY	…
HuggingFace	HUGGINGFACE_API_KEY	hf_…
Mistral	MISTRAL_API_KEY	…
NVIDIA	NVIDIA_API_KEY	nvapi-…
Ollama	OLLAMA_HOST	http://localhost:11434
OpenRouter	OPENROUTER_API_KEY	…
Together	TOGETHER_API_KEY	…
Cerebras	CEREBRAS_API_KEY	…
DeepInfra	DEEPINFRA_API_KEY	…
SambaNova	SAMBANOVA_API_KEY	…
AWS Bedrock	AWS credentials	Via AWS CLI/SDK
Azure AI	Azure credentials	Via Azure CLI/SDK
IBM WatsonX	IBM_WATSONX_API_KEY	…
Meta Llama	LLAMA_API_KEY	…

Note: Only configure the API keys for providers you plan to use.

Examples

Text Generation

# Using OpenAI
provider: openai
model: gpt-4o-mini
prompt: Write a haiku about coding

# Using Anthropic
provider: anthropic
model: claude-3-5-sonnet-20241022
prompt: Explain quantum computing in simple terms

# Using Google
provider: google
model: gemini-2.0-flash-exp
prompt: Create a recipe for chocolate chip cookies

Image Generation

# Using DALL-E 3
provider: openai
model: dall-e-3
prompt: A serene Japanese garden with cherry blossoms

# Using DALL-E 2
provider: openai
model: dall-e-2
prompt: A futuristic cityscape at sunset

Development

Prerequisites

• Python 3.11 or higher
• uv package manager

Setup

git clone https://github.com/gwbischof/outsource-mcp.git
cd outsource-mcp
uv sync

Testing with MCP Inspector

The MCP Inspector allows you to test the server interactively:

mcp dev server.py

Running Tests

The test suite includes integration tests that verify both text and image generation:

# Run all tests
uv run pytest

Note: Integration tests require API keys to be set in your environment.

Troubleshooting

Common Issues

1. “Error: Unknown provider”

   • Check that you’re using a supported provider name from the list above
   • Provider names are case-insensitive

2. “Error: OpenAI API error”

   • Verify your API key is correctly set in the environment variables
   • Check that your API key has access to the requested model
   • Ensure you have sufficient credits/quota

3. “Error: No image was generated”

   • This can happen if the image generation request fails
   • Try a simpler prompt or different model (dall-e-2 vs dall-e-3)

4. Environment variables not working

   • Make sure to restart your MCP client after updating the configuration
   • Verify the configuration file location for your specific MCP client
   • Check that the environment variables are properly formatted in the configuration

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.