4d2ad48638
When using the Gemini MCP server from Claude Code, it now automatically injects a developer-focused system prompt similar to Claude Code's own behavior. This ensures Gemini responds with the same developer mindset: - Expert software development knowledge - Clean code practices - Debugging and problem-solving focus - Clear technical explanations - Architecture and design understanding - Performance optimization expertise The system prompt is automatically applied when no custom system prompt is provided, making the integration seamless for Claude Code users. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
Test script to verify developer context is properly injected
|
|
"""
|
|
|
|
import os
|
|
import asyncio
|
|
from gemini_server import configure_gemini, handle_call_tool
|
|
|
|
|
|
async def test_developer_context():
|
|
"""Test the developer context system prompt"""
|
|
print("Testing Developer Context in Gemini MCP Server...")
|
|
print("-" * 50)
|
|
|
|
# Test configuration
|
|
try:
|
|
configure_gemini()
|
|
print("✓ Gemini API configured successfully")
|
|
except Exception as e:
|
|
print(f"✗ Failed to configure Gemini API: {e}")
|
|
return
|
|
|
|
# Test 1: Chat without explicit system prompt (should use developer prompt)
|
|
print("\n1. Testing chat WITHOUT system prompt (should auto-inject developer context)...")
|
|
result = await handle_call_tool("chat", {
|
|
"prompt": "Write a Python function to reverse a linked list. Include comments.",
|
|
"temperature": 0.3,
|
|
"max_tokens": 500
|
|
})
|
|
print("Response preview:")
|
|
print(result[0].text[:400] + "..." if len(result[0].text) > 400 else result[0].text)
|
|
|
|
# Test 2: Chat WITH explicit system prompt (should use provided prompt)
|
|
print("\n2. Testing chat WITH custom system prompt...")
|
|
result = await handle_call_tool("chat", {
|
|
"prompt": "Write a haiku about coding",
|
|
"system_prompt": "You are a creative poet who writes about technology.",
|
|
"temperature": 0.9,
|
|
"max_tokens": 100
|
|
})
|
|
print("Response:")
|
|
print(result[0].text)
|
|
|
|
# Test 3: Code analysis without system prompt (should use developer prompt)
|
|
print("\n3. Testing analyze_code WITHOUT system prompt...")
|
|
test_code = '''
|
|
def bubble_sort(arr):
|
|
n = len(arr)
|
|
for i in range(n):
|
|
for j in range(0, n-i-1):
|
|
if arr[j] > arr[j+1]:
|
|
arr[j], arr[j+1] = arr[j+1], arr[j]
|
|
return arr
|
|
'''
|
|
|
|
result = await handle_call_tool("analyze_code", {
|
|
"code": test_code,
|
|
"question": "Review this code and suggest improvements",
|
|
"temperature": 0.3
|
|
})
|
|
print("Response preview:")
|
|
print(result[0].text[:500] + "..." if len(result[0].text) > 500 else result[0].text)
|
|
|
|
# Test 4: Code analysis WITH custom system prompt
|
|
print("\n4. Testing analyze_code WITH custom system prompt...")
|
|
result = await handle_call_tool("analyze_code", {
|
|
"code": test_code,
|
|
"question": "Is this code correct?",
|
|
"system_prompt": "You are a beginner-friendly tutor. Explain things simply.",
|
|
"temperature": 0.5
|
|
})
|
|
print("Response preview:")
|
|
print(result[0].text[:400] + "..." if len(result[0].text) > 400 else result[0].text)
|
|
|
|
print("\n" + "-" * 50)
|
|
print("Developer context tests completed!")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# Check for API key
|
|
if not os.getenv("GEMINI_API_KEY"):
|
|
print("Error: GEMINI_API_KEY environment variable is not set")
|
|
print("Please set it with: export GEMINI_API_KEY='your-api-key'")
|
|
exit(1)
|
|
|
|
asyncio.run(test_developer_context()) |