This directory contains example configurations for different LLM providers.
-
Choose your provider:
openai_config.json- OpenAI GPT models (requires API key)anthropic_config.json- Anthropic Claude models (requires API key)ollama_config.json- Ollama local models (free, requires Ollama installed)
-
Copy to your config directory:
# For macOS/Linux cp openai_config.json ~/.mcpproxy/mcp_config.json # Or for Windows copy openai_config.json %USERPROFILE%\.mcpproxy\mcp_config.json
-
Add your API key (OpenAI or Anthropic):
- Edit the config file
- Replace
YOUR-KEY-HEREwith your actual API key
-
Restart mcpproxy:
pkill mcpproxy ./mcpproxy serve
- Pros: Fast, reliable, good general performance
- Cons: Requires paid API key
- Best for: Most users, production use
- Get API key: https://platform.openai.com/api-keys
- Pros: Excellent reasoning, advanced capabilities
- Cons: Requires paid API key
- Best for: Complex diagnostic tasks, advanced reasoning
- Get API key: https://console.anthropic.com/
- Pros: Free, fully local, privacy-focused
- Cons: Requires local installation, slower on weak hardware
- Best for: Privacy-sensitive environments, offline use
- Setup:
# Install Ollama brew install ollama # macOS # Or download from https://ollama.ai # Start Ollama ollama serve # Pull a model ollama pull llama2
All config files support these LLM parameters:
{
"llm": {
"provider": "openai|anthropic|ollama",
"model": "model-name",
"temperature": 0.7,
"max_tokens": 2000
}
}- 0.0: Deterministic, focused responses
- 0.7: Balanced (recommended)
- 1.0: Creative, varied responses
- Controls response length
- Higher = longer responses (but more expensive)
- Default: 2000 tokens (~1500 words)
