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:

Generate text: Use the outsource_text tool with provider "openai", model "gpt-4o-mini", and prompt "Write a haiku about coding"
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

"Error: Unknown provider"
- Check that you're using a supported provider name from the list above
- Provider names are case-insensitive
"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
"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)
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.

MCP Servers