MCP DeepInfra AI Tools Server

Instructions

Implementation Reference

• src/mcp_deepinfra/server.py:47-62 (handler)

  The generate_image tool handler, registered with @app.tool(), generates an image URL from a text prompt using DeepInfra's OpenAI-compatible images.generate API.

  @app.tool()
  async def generate_image(prompt: str) -> str:
      """Generate an image from a text prompt using DeepInfra OpenAI-compatible API."""
      model = DEFAULT_MODELS["generate_image"]
      try:
          response = await client.images.generate(
              model=model,
              prompt=prompt,
              n=1,
          )
          if response.data:
              return f"Generated image URL: {response.data[0].url}"
          else:
              return "No image generated"
      except Exception as e:
          return f"Error generating image: {type(e).__name__}: {str(e)}"

• src/mcp_deepinfra/server.py:31-42 (helper)

  Global DEFAULT_MODELS dictionary providing the default model ('Bria/Bria-3.2') for the generate_image tool.

  DEFAULT_MODELS = {
      "generate_image": os.getenv("MODEL_GENERATE_IMAGE", "Bria/Bria-3.2"),
      "text_generation": os.getenv("MODEL_TEXT_GENERATION", "meta-llama/Llama-2-7b-chat-hf"),
      "embeddings": os.getenv("MODEL_EMBEDDINGS", "sentence-transformers/all-MiniLM-L6-v2"),
      "speech_recognition": os.getenv("MODEL_SPEECH_RECOGNITION", "openai/whisper-large-v3"),
      "zero_shot_image_classification": os.getenv("MODEL_ZERO_SHOT_IMAGE_CLASSIFICATION", "openai/gpt-4o-mini"),
      "object_detection": os.getenv("MODEL_OBJECT_DETECTION", "openai/gpt-4o-mini"),
      "image_classification": os.getenv("MODEL_IMAGE_CLASSIFICATION", "openai/gpt-4o-mini"),
      "text_classification": os.getenv("MODEL_TEXT_CLASSIFICATION", "microsoft/DialoGPT-medium"),
      "token_classification": os.getenv("MODEL_TOKEN_CLASSIFICATION", "microsoft/DialoGPT-medium"),
      "fill_mask": os.getenv("MODEL_FILL_MASK", "microsoft/DialoGPT-medium"),
  }