"""Example of using MCP Codebase Insight with Claude."""
import json
import httpx
import os
from typing import Dict, Any
import asyncio
# Configure server URL
SERVER_URL = os.getenv("MCP_SERVER_URL", "http://localhost:3000")
async def call_tool(name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Call a tool endpoint on the server."""
async with httpx.AsyncClient() as client:
response = await client.post(
f"{SERVER_URL}/tools/{name}",
json={
"name": name,
"arguments": arguments
}
)
response.raise_for_status()
return response.json()
async def analyze_code(code: str, context: Dict[str, Any] = None) -> Dict[str, Any]:
"""Analyze code using the server."""
return await call_tool("analyze-code", {
"code": code,
"context": context or {}
})
async def search_knowledge(query: str, pattern_type: str = None) -> Dict[str, Any]:
"""Search knowledge base."""
return await call_tool("search-knowledge", {
"query": query,
"type": pattern_type,
"limit": 5
})
async def create_adr(
title: str,
context: Dict[str, Any],
options: list,
decision: str
) -> Dict[str, Any]:
"""Create an ADR."""
return await call_tool("create-adr", {
"title": title,
"context": context,
"options": options,
"decision": decision
})
async def debug_issue(
description: str,
issue_type: str = None,
context: Dict[str, Any] = None
) -> Dict[str, Any]:
"""Debug an issue."""
return await call_tool("debug-issue", {
"description": description,
"type": issue_type,
"context": context or {}
})
async def get_task_status(task_id: str) -> Dict[str, Any]:
"""Get task status and results."""
return await call_tool("get-task", {
"task_id": task_id
})
async def main():
"""Example usage."""
try:
# Example code analysis
code = """
def calculate_fibonacci(n: int) -> int:
if n <= 1:
return n
return calculate_fibonacci(n-1) + calculate_fibonacci(n-2)
"""
print("\nAnalyzing code...")
result = await analyze_code(code)
print(json.dumps(result, indent=2))
# Example knowledge search
print("\nSearching knowledge base...")
result = await search_knowledge(
query="What are the best practices for error handling in Python?",
pattern_type="code"
)
print(json.dumps(result, indent=2))
# Example ADR creation
print("\nCreating ADR...")
result = await create_adr(
title="Use FastAPI for REST API",
context={
"problem": "Need a modern Python web framework",
"constraints": ["Must be async", "Must have good documentation"]
},
options=[
{
"title": "FastAPI",
"pros": ["Async by default", "Great docs", "Type hints"],
"cons": ["Newer framework"]
},
{
"title": "Flask",
"pros": ["Mature", "Simple"],
"cons": ["Not async by default"]
}
],
decision="We will use FastAPI for its async support and type hints"
)
print(json.dumps(result, indent=2))
# Example debugging
print("\nDebugging issue...")
result = await debug_issue(
description="Application crashes when processing large files",
issue_type="performance",
context={
"file_size": "2GB",
"memory_usage": "8GB",
"error": "MemoryError"
}
)
print(json.dumps(result, indent=2))
except Exception as e:
print(f"Error: {e}")
if __name__ == "__main__":
asyncio.run(main())