forked from MCP/llm-fusion-mcp
Ryan Malloy
c335ba0e1e
- Unified access to 4 major LLM providers (Gemini, OpenAI, Anthropic, Grok) - Real-time streaming support across all providers - Multimodal capabilities (text, images, audio) - Intelligent document processing with smart chunking - Production-ready with health monitoring and error handling - Full OpenAI ecosystem integration (Assistants, DALL-E, Whisper) - Vector embeddings and semantic similarity - Session-based API key management - Built with FastMCP and modern Python tooling 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
"""OpenAI-specific tools for the Multi-LLM MCP Server - Simple Working Version"""
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import os
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from typing import Dict, Any, Optional
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from openai import OpenAI
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def get_openai_client() -> OpenAI:
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"""Get configured OpenAI client with API key from environment or session."""
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api_key = os.getenv("OPENAI_API_KEY")
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if not api_key:
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raise ValueError("No OpenAI API key found. Set OPENAI_API_KEY environment variable.")
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return OpenAI(api_key=api_key)
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def register_simple_openai_tools(mcp):
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"""Register simplified OpenAI tools that work with FastMCP."""
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@mcp.tool()
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def openai_test_connection() -> Dict[str, Any]:
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"""Test OpenAI API connection and list available models.
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This is a simple test tool to verify the OpenAI integration is working.
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Returns information about available models and API connectivity.
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"""
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try:
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client = get_openai_client()
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models = client.models.list()
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model_names = [model.id for model in models.data[:10]] # First 10 models
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return {
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"status": "connected",
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"models_sample": model_names,
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"total_models": len(models.data),
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"success": True
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}
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except Exception as e:
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return {
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"status": "error",
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"error": str(e),
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"success": False
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}
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@mcp.tool()
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def openai_generate_simple(prompt: str, model: str = "gpt-4o-mini") -> Dict[str, Any]:
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"""Generate text using OpenAI API with simple interface.
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Args:
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prompt: The text prompt to generate from
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model: OpenAI model to use (default: gpt-4o-mini)
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Returns:
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Dict with generated text and metadata
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"""
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try:
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client = get_openai_client()
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response = client.chat.completions.create(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=1000
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)
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return {
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"text": response.choices[0].message.content,
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"model": model,
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"usage": {
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"prompt_tokens": response.usage.prompt_tokens,
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"completion_tokens": response.usage.completion_tokens,
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"total_tokens": response.usage.total_tokens
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},
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"success": True
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}
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except Exception as e:
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return {
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"error": str(e),
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"success": False
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}
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print("✅ Simple OpenAI tools registered successfully!") |