Files
my-pal-mcp-server/server.py
Fahad c03af1629f fix: apply isort formatting to fix CI linting
Applied isort to properly sort all imports according to PEP8:
- Standard library imports first
- Third-party imports second
- Local imports last
- Alphabetical ordering within each group

All tests still passing after import reordering.
2025-06-08 22:32:27 +04:00

267 lines
8.2 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
import google.generativeai as 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, 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(),
}
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."
)
genai.configure(api_key=api_key)
logger.info("Gemini API configured successfully")
@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="chat",
description=(
"GENERAL CHAT - Have a conversation with Gemini about any development topic. "
"Use for explanations, brainstorming, or general questions. "
"Triggers: 'ask gemini', 'explain', 'what is', 'how do I'."
),
inputSchema={
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "Your question or topic",
},
"context_files": {
"type": "array",
"items": {"type": "string"},
"description": "Optional files for context",
},
"temperature": {
"type": "number",
"description": "Response creativity (0-1, default 0.5)",
"minimum": 0,
"maximum": 1,
},
},
"required": ["prompt"],
},
),
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 == "chat":
return await handle_chat(arguments)
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_chat(arguments: Dict[str, Any]) -> List[TextContent]:
"""Handle general chat requests"""
from config import TEMPERATURE_BALANCED
from utils import read_files
prompt = arguments.get("prompt", "")
context_files = arguments.get("context_files", [])
temperature = arguments.get("temperature", TEMPERATURE_BALANCED)
# Build context if files provided
full_prompt = prompt
if context_files:
file_content, _ = read_files(context_files)
full_prompt = f"{prompt}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ==="
try:
model = genai.GenerativeModel(
model_name=DEFAULT_MODEL,
generation_config={
"temperature": temperature,
"max_output_tokens": 8192,
"candidate_count": 1,
},
)
response = model.generate_content(full_prompt)
if response.candidates and response.candidates[0].content.parts:
text = response.candidates[0].content.parts[0].text
else:
text = "Response blocked or incomplete"
return [TextContent(type="text", text=text)]
except Exception as e:
return [TextContent(type="text", text=f"Error in chat: {str(e)}")]
async def handle_list_models() -> List[TextContent]:
"""List available Gemini models"""
try:
import json
models = []
for model_info in genai.list_models():
if (
hasattr(model_info, "supported_generation_methods")
and "generateContent"
in model_info.supported_generation_methods
):
models.append(
{
"name": model_info.name,
"display_name": getattr(
model_info, "display_name", "Unknown"
),
"description": getattr(
model_info, "description", "No description"
),
"is_default": model_info.name.endswith(DEFAULT_MODEL),
}
)
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())