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docs: Add practical usage tips and clean up test files

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- Added comprehensive usage tips section to README
  - Effective command examples
  - Common workflows for Claude Code users
  - Best practices for combining Claude and Gemini
  - Specific examples for different use cases

- Removed all test files (test_*.py) that were only for development
  - test_server.py
  - test_enhanced.py
  - test_developer_context.py
  - test_optimized.py

The repository now contains only the essential files needed for users
to run the Gemini MCP server with Claude Code.

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

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Fahad
2025-06-08 20:20:57 +04:00
parent 149a58d042
commit 573dbf8f40
5 changed files with 53 additions and 352 deletions
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53
README.md
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@@ -171,6 +171,59 @@ You: "Use Gemini to analyze all files in /src/core/ and create an architecture d
You: "Have Gemini profile this codebase and suggest the top 5 performance improvements"
```
## 💡 Practical Usage Tips
### Effective Commands
Be specific about what you want from Gemini:
- ✅ "Ask Gemini to identify memory leaks in this code"
- ❌ "Ask Gemini about this"
### Common Workflows
#### 1. **Extended Code Review**
```
You: "Implement feature X"
Claude: [implements]
You: "Use Gemini to review this implementation for scalability issues"
Gemini: [provides detailed feedback]
You: "Based on Gemini's feedback, improve the implementation"
Claude: [refines based on feedback]
```
#### 2. **Large File Analysis**
```
"Use Gemini to analyze /path/to/large/file.py and summarize its architecture"
"Have Gemini trace all function calls in this module"
"Ask Gemini to identify unused code in this file"
```
#### 3. **Multi-File Context**
```
"Use Gemini to analyze how auth.py, users.py, and permissions.py work together"
"Have Gemini map the data flow between these components"
"Ask Gemini to find all circular dependencies in /src"
```
#### 4. **Second Opinion & Validation**
```
"I'm planning to refactor using pattern X. Ask Gemini for potential issues"
"Use Gemini to validate my database schema design"
"Have Gemini suggest alternative approaches to this algorithm"
```
#### 5. **Security & Performance Audits**
```
"Use Gemini to security audit this authentication flow"
"Have Gemini identify performance bottlenecks in this codebase"
"Ask Gemini to check for common security vulnerabilities"
```
### Best Practices
- Use Gemini when you need analysis beyond Claude's context window
- Leverage Gemini's 1M token limit for whole-codebase analysis
- Combine both assistants: Claude for implementation, Gemini for review
- Be specific in your requests for more accurate responses
## 📝 Notes
- Gemini 2.5 Pro Preview may occasionally block certain prompts due to safety filters

87
test_developer_context.py
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@@ -1,87 +0,0 @@
#!/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())

111
test_enhanced.py
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@@ -1,111 +0,0 @@
#!/usr/bin/env python3
"""
Enhanced test script for Gemini MCP Server with code analysis features
"""
import os
import asyncio
import json
from pathlib import Path
from gemini_server import configure_gemini, handle_call_tool, handle_list_tools
async def test_enhanced_features():
"""Test the enhanced server functionality"""
print("Testing Enhanced 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 listing tools (should now include analyze_code)
print("\n1. Testing list_tools...")
tools = await handle_list_tools()
print(f"✓ Found {len(tools)} tools:")
for tool in tools:
print(f" - {tool.name}: {tool.description}")
# Test chat with 2.5 Pro Preview default
print("\n2. Testing chat with default 2.5 Pro Preview...")
chat_result = await handle_call_tool("chat", {
"prompt": "What model are you? Please confirm you're Gemini 2.5 Pro Preview.",
"temperature": 0.3,
"max_tokens": 200
})
print("✓ Chat response:")
print(chat_result[0].text[:200] + "..." if len(chat_result[0].text) > 200 else chat_result[0].text)
# Create a test file for code analysis
test_file = Path("test_sample.py")
test_code = '''def fibonacci(n):
"""Calculate fibonacci number at position n"""
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
def factorial(n):
"""Calculate factorial of n"""
if n <= 1:
return 1
return n * factorial(n-1)
# Test the functions
print(f"Fibonacci(10): {fibonacci(10)}")
print(f"Factorial(5): {factorial(5)}")
'''
with open(test_file, 'w') as f:
f.write(test_code)
# Test analyze_code with file
print("\n3. Testing analyze_code with file...")
analysis_result = await handle_call_tool("analyze_code", {
"files": [str(test_file)],
"question": "What are the time complexities of these functions? Can you suggest optimizations?",
"temperature": 0.3,
"max_tokens": 500
})
print("✓ Code analysis response:")
print(analysis_result[0].text[:400] + "..." if len(analysis_result[0].text) > 400 else analysis_result[0].text)
# Test analyze_code with direct code
print("\n4. Testing analyze_code with direct code...")
analysis_result = await handle_call_tool("analyze_code", {
"code": "class Stack:\n def __init__(self):\n self.items = []\n def push(self, item):\n self.items.append(item)\n def pop(self):\n return self.items.pop() if self.items else None",
"question": "Is this a good implementation of a stack? What improvements would you suggest?",
"temperature": 0.3
})
print("✓ Direct code analysis response:")
print(analysis_result[0].text[:400] + "..." if len(analysis_result[0].text) > 400 else analysis_result[0].text)
# Test large context (simulate)
print("\n5. Testing context size estimation...")
large_code = "x = 1\n" * 100000 # ~600K characters, ~150K tokens
analysis_result = await handle_call_tool("analyze_code", {
"code": large_code,
"question": "How many assignment statements are in this code?",
"temperature": 0.1
})
print("✓ Large context test:")
print(analysis_result[0].text[:200] + "..." if len(analysis_result[0].text) > 200 else analysis_result[0].text)
# Clean up test file
test_file.unlink()
print("\n" + "-" * 50)
print("All enhanced 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_enhanced_features())

84
test_optimized.py
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@@ -1,84 +0,0 @@
#!/usr/bin/env python3
"""
Test script for optimized Claude Code settings
"""
import os
import asyncio
from gemini_server import configure_gemini, handle_call_tool
async def test_optimized_settings():
"""Test the optimized temperature and developer settings"""
print("Testing Optimized Claude Code Settings...")
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: Default chat temperature (should be 0.5)
print("\n1. Testing chat with default temperature (0.5)...")
result = await handle_call_tool("chat", {
"prompt": "Explain the concept of dependency injection in one paragraph. Be concise but thorough."
})
print("Response preview (should be balanced - accurate but not robotic):")
print(result[0].text[:300] + "..." if len(result[0].text) > 300 else result[0].text)
# Test 2: Code analysis with low temperature (0.2)
print("\n2. Testing code analysis with default low temperature (0.2)...")
code = '''
async def fetch_user_data(user_id: str, cache=None):
if cache and user_id in cache:
return cache[user_id]
response = await http_client.get(f"/api/users/{user_id}")
user_data = response.json()
if cache:
cache[user_id] = user_data
return user_data
'''
result = await handle_call_tool("analyze_code", {
"code": code,
"question": "Identify potential issues and suggest improvements"
})
print("Response preview (should be precise and technical):")
print(result[0].text[:400] + "..." if len(result[0].text) > 400 else result[0].text)
# Test 3: Creative task with higher temperature
print("\n3. Testing creative task with custom higher temperature...")
result = await handle_call_tool("chat", {
"prompt": "Suggest 3 innovative ways to implement a rate limiter",
"temperature": 0.8
})
print("Response preview (should be more creative):")
print(result[0].text[:400] + "..." if len(result[0].text) > 400 else result[0].text)
# Test 4: Verify developer context is applied
print("\n4. Testing developer context (no system prompt)...")
result = await handle_call_tool("chat", {
"prompt": "What's the time complexity of quicksort?",
"temperature": 0.3
})
print("Response (should be technical and developer-focused):")
print(result[0].text[:300] + "..." if len(result[0].text) > 300 else result[0].text)
print("\n" + "-" * 50)
print("Optimized settings test 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_optimized_settings())

70
test_server.py
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@@ -1,70 +0,0 @@
#!/usr/bin/env python3
"""
Test script for Gemini MCP Server
"""
import os
import asyncio
import json
from gemini_server import configure_gemini, handle_call_tool, handle_list_tools
async def test_server():
"""Test the server functionality"""
print("Testing 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 listing tools
print("\n1. Testing list_tools...")
tools = await handle_list_tools()
print(f"✓ Found {len(tools)} tools:")
for tool in tools:
print(f" - {tool.name}: {tool.description}")
# Test list_models
print("\n2. Testing list_models tool...")
models_result = await handle_call_tool("list_models", {})
print("✓ Available models:")
print(models_result[0].text)
# Test chat
print("\n3. Testing chat tool...")
chat_result = await handle_call_tool("chat", {
"prompt": "What is the capital of France?",
"temperature": 0.3,
"max_tokens": 50
})
print("✓ Chat response:")
print(chat_result[0].text)
# Test chat with system prompt
print("\n4. Testing chat with system prompt...")
chat_result = await handle_call_tool("chat", {
"prompt": "What's 2+2?",
"system_prompt": "You are a helpful math tutor. Always explain your reasoning step by step.",
"temperature": 0.3,
"max_tokens": 200
})
print("✓ Chat response with system prompt:")
print(chat_result[0].text)
print("\n" + "-" * 50)
print("All 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_server())