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Caution Review failedThe pull request is closed. WalkthroughThis update replaces all print statements in the framework with debug-level logging, adds logging configuration examples to the documentation and example scripts, and introduces new web-based example scripts using FastAPI and tool integration. The README is expanded with detailed guidance on logging, tool creation, server hosting, and middleware customization. Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant MCP_Server as MCP Server (pymcp.server)
participant Tool as callFlaskHelloTool
participant FlaskAPI as Flask API Server
User->>MCP_Server: Sends request to callFlaskHelloTool
MCP_Server->>Tool: Invokes callFlaskHelloTool()
Tool->>FlaskAPI: HTTP GET /hello
FlaskAPI-->>Tool: JSON {"message": "..."}
Tool-->>MCP_Server: Returns formatted message
MCP_Server-->>User: Responds with result
Assessment against linked issues
Assessment against linked issues: Out-of-scope changes
Poem
Warning There were issues while running some tools. Please review the errors and either fix the tool's configuration or disable the tool if it's a critical failure. 🔧 Pylint (3.3.7)pymcp/server.py📜 Recent review detailsConfiguration used: CodeRabbit UI 📒 Files selected for processing (1)
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Actionable comments posted: 1
🧹 Nitpick comments (3)
pymcp/server.py (1)
153-155: Consider reducing log verbosity for production.While detailed logging is helpful for debugging, logging full tool schemas might be too verbose for production environments. Consider using a more concise format or making this configurable.
- logging.debug(f"[TOOLS] Sending {len(tools_list)} tools to Cursor") - logging.debug(f"[TOOLS] Tool names: {[t['name'] for t in tools_list]}") - logging.debug(f"[TOOLS] Tool schemas: {json.dumps(tools_list, indent=2)}") + logging.debug(f"[TOOLS] Sending {len(tools_list)} tools to Cursor: {[t['name'] for t in tools_list]}") + if logging.getLogger().isEnabledFor(logging.DEBUG): + logging.debug(f"[TOOLS] Tool schemas: {json.dumps(tools_list, indent=2)}")example/web-based/run_mcp_with_flask_call.py (2)
11-11: Consider increasing the timeout for better reliability.A 2-second timeout might be too short for network requests, especially in slower environments. Consider increasing it to 5-10 seconds.
- resp = requests.get("http://127.0.0.1:5005/hello", timeout=2) + resp = requests.get("http://127.0.0.1:5005/hello", timeout=5)
22-24: Consider using logging instead of print for consistency.Since the PR migrates from print to logging, consider using logging for this informational message to maintain consistency.
- print( - "[INFO] Make sure to start the Flask API server (flask_api_server.py) before running this example." - ) + import logging + logging.info( + "Make sure to start the Flask API server (flask_api_server.py) before running this example." + )
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📒 Files selected for processing (5)
README.md(2 hunks)example/run_server.py(1 hunks)example/web-based/fast_api_server.py(1 hunks)example/web-based/run_mcp_with_flask_call.py(1 hunks)pymcp/server.py(4 hunks)
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🧬 Code Graph Analysis (1)
example/web-based/run_mcp_with_flask_call.py (1)
pymcp/registry.py (1)
register(8-32)
🪛 LanguageTool
README.md
[uncategorized] ~71-~71: Possible missing comma found.
Context: ...add this before running the server with Uvicorn as shown above. Request flow of an exa...
(AI_HYDRA_LEO_MISSING_COMMA)
🔇 Additional comments (10)
example/run_server.py (1)
1-1: LGTM: Proper logging configuration setup.The logging import and basic configuration are correctly placed at the beginning of the script, following Python best practices for logging setup.
Also applies to: 6-6
pymcp/server.py (2)
3-3: LGTM: Proper logging import added.The logging import is correctly placed with other standard library imports.
37-38: LGTM: Good migration from print to logging.The conversion from print statements to proper logging is well done and provides better observability.
example/web-based/fast_api_server.py (1)
1-15: LGTM: Clean FastAPI server implementation.The code follows FastAPI best practices with proper imports, async endpoint definition, and standard Uvicorn configuration. The implementation is minimal and focused.
example/web-based/run_mcp_with_flask_call.py (1)
7-16: LGTM: Well-structured tool implementation with good error handling.The tool follows the registry pattern correctly and includes appropriate error handling with timeout configuration.
README.md (5)
13-19: LGTM: Excellent logging configuration guidance.The early placement of logging configuration instructions is perfect, helping users understand how to enable debug output before they encounter issues.
30-42: LGTM: Clear and practical tool creation example.The example demonstrates the registry pattern effectively and provides users with a straightforward template for creating their own tools.
43-53: LGTM: Helpful server hosting instructions.The FastAPI and Uvicorn hosting section provides clear guidance for users who want to customize their server deployment.
55-71: LGTM: Useful middleware configuration example.The middleware example shows users how to extend the framework's capabilities, which is valuable for customization.
76-86: LGTM: Comprehensive logging documentation.The final logging section reinforces the configuration requirements and provides users with clear guidance on controlling log verbosity.
2 participants
fixes #6
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New Features
Documentation
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