Grok MCP

Implementation Reference

• src/server.py:88-110 (handler)

  The implementation of the `list_models` tool which queries the xAI API for both language and image generation models and formats the results for the MCP output.

  @mcp.tool(annotations=READONLY)
  async def list_models():
  
      client = Client(api_key=XAI_API_KEY)
      models_info = []
  
      models_info.append("# Language Models\n")
      for m in client.models.list_language_models():
          date = m.created.ToDatetime().strftime('%d %b %Y')
          inp = m.prompt_text_token_price / 10000
          out = m.completion_text_token_price / 10000
          models_info.append(f"**{m.name}** — {date}")
          models_info.append(f"  Input: ${inp:g}/M · Output: ${out:g}/M\n")
  
      models_info.append("# Image Generation Models\n")
      for m in client.models.list_image_generation_models():
          date = m.created.ToDatetime().strftime('%d %b %Y')
          price = m.image_price / 10000000000
          models_info.append(f"**{m.name}** — {date}")
          models_info.append(f"  ${price:g} per image\n")
  
      client.close()
      return "\n".join(models_info)