Files
my-pal-mcp-server/server.py
Fahad 299f7d3897 feat: add Claude-Gemini collaboration and chat capabilities
- Add collaboration demo showing dynamic context requests
- Implement chat tool for general conversations and brainstorming
- Add tool selection guide with clear boundaries
- Introduce models configuration system
- Update prompts for better tool descriptions
- Refactor server to remove redundant functionality
- Add comprehensive tests for collaboration features
- Enhance base tool with collaborative features

This enables Claude to request additional context from Gemini
during tool execution, improving analysis quality and accuracy.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-06-09 11:17:26 +04:00

223 lines
6.5 KiB
Python

"""
Gemini MCP Server - Main server implementation
"""
import asyncio
import logging
import os
import sys
from datetime import datetime
from typing import Any, Dict, List
from google import genai
from mcp.server import Server
from mcp.server.models import InitializationOptions
from mcp.server.stdio import stdio_server
from mcp.types import TextContent, Tool
from config import (
DEFAULT_MODEL,
MAX_CONTEXT_TOKENS,
__author__,
__updated__,
__version__,
)
from tools import AnalyzeTool, ChatTool, DebugIssueTool, ReviewCodeTool, ThinkDeeperTool
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Create the MCP server instance
server: Server = Server("gemini-server")
# Initialize tools
TOOLS = {
"think_deeper": ThinkDeeperTool(),
"review_code": ReviewCodeTool(),
"debug_issue": DebugIssueTool(),
"analyze": AnalyzeTool(),
"chat": ChatTool(),
}
def configure_gemini():
"""Configure Gemini API with the provided API key"""
api_key = os.getenv("GEMINI_API_KEY")
if not api_key:
raise ValueError(
"GEMINI_API_KEY environment variable is required. "
"Please set it with your Gemini API key."
)
# API key is used when creating clients in tools
logger.info("Gemini API key found")
@server.list_tools()
async def handle_list_tools() -> List[Tool]:
"""List all available tools with verbose descriptions"""
tools = []
for tool in TOOLS.values():
tools.append(
Tool(
name=tool.name,
description=tool.description,
inputSchema=tool.get_input_schema(),
)
)
# Add utility tools
tools.extend(
[
Tool(
name="list_models",
description=(
"LIST AVAILABLE MODELS - Show all Gemini models you can use. "
"Lists model names, descriptions, and which one is the default."
),
inputSchema={"type": "object", "properties": {}},
),
Tool(
name="get_version",
description=(
"VERSION & CONFIGURATION - Get server version, configuration details, "
"and list of available tools. Useful for debugging and understanding capabilities."
),
inputSchema={"type": "object", "properties": {}},
),
]
)
return tools
@server.call_tool()
async def handle_call_tool(name: str, arguments: Dict[str, Any]) -> List[TextContent]:
"""Handle tool execution requests"""
# Handle dynamic tools
if name in TOOLS:
tool = TOOLS[name]
return await tool.execute(arguments)
# Handle static tools
elif name == "list_models":
return await handle_list_models()
elif name == "get_version":
return await handle_get_version()
else:
return [TextContent(type="text", text=f"Unknown tool: {name}")]
async def handle_list_models() -> List[TextContent]:
"""List available Gemini models"""
try:
import json
# Get API key
api_key = os.getenv("GEMINI_API_KEY")
if not api_key:
return [TextContent(type="text", text="Error: GEMINI_API_KEY not set")]
client = genai.Client(api_key=api_key)
models = []
# List models using the new API
try:
model_list = client.models.list()
for model_info in model_list:
models.append(
{
"name": getattr(model_info, "id", "Unknown"),
"display_name": getattr(
model_info,
"display_name",
getattr(model_info, "id", "Unknown"),
),
"description": getattr(
model_info, "description", "No description"
),
"is_default": getattr(model_info, "id", "").endswith(
DEFAULT_MODEL
),
}
)
except Exception:
# Fallback: return some known models
models = [
{
"name": "gemini-2.5-pro-preview-06-05",
"display_name": "Gemini 2.5 Pro",
"description": "Latest Gemini 2.5 Pro model",
"is_default": True,
},
{
"name": "gemini-2.0-flash-thinking-exp",
"display_name": "Gemini 2.0 Flash Thinking",
"description": "Enhanced reasoning model",
"is_default": False,
},
]
return [TextContent(type="text", text=json.dumps(models, indent=2))]
except Exception as e:
return [TextContent(type="text", text=f"Error listing models: {str(e)}")]
async def handle_get_version() -> List[TextContent]:
"""Get version and configuration information"""
version_info = {
"version": __version__,
"updated": __updated__,
"author": __author__,
"default_model": DEFAULT_MODEL,
"max_context_tokens": f"{MAX_CONTEXT_TOKENS:,}",
"python_version": f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}",
"server_started": datetime.now().isoformat(),
"available_tools": list(TOOLS.keys()) + ["chat", "list_models", "get_version"],
}
text = f"""Gemini MCP Server v{__version__}
Updated: {__updated__}
Author: {__author__}
Configuration:
- Default Model: {DEFAULT_MODEL}
- Max Context: {MAX_CONTEXT_TOKENS:,} tokens
- Python: {version_info['python_version']}
- Started: {version_info['server_started']}
Available Tools:
{chr(10).join(f" - {tool}" for tool in version_info['available_tools'])}
For updates, visit: https://github.com/BeehiveInnovations/gemini-mcp-server"""
return [TextContent(type="text", text=text)]
async def main():
"""Main entry point for the server"""
# Configure Gemini API
configure_gemini()
# Run the server using stdio transport
async with stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="gemini",
server_version=__version__,
capabilities={"tools": {}},
),
)
if __name__ == "__main__":
asyncio.run(main())