- Refined `mock_multi_agent.py` to parse and route stock-specific inputs correctly
- Addressed issue where StockAnalyst returned fallback prompts instead of actionable responses
- Improved overall agent logic for financial data interpretation and reply generation
- Updated `mock_multi_agent.py` to provide meaningful responses to capability-related queries
- Ensured agents clearly state what operations they can perform (e.g., add, multiply, divide)
- Fixed initialization issues in `mock_stock_server.py`
- Modified `mock_multi_agent.py` to handle responses from both math and stock servers
- Enhanced agent prompts and results processing for multi-server context
- Resolved TypeError due to passing 4 arguments to a 3-parameter constructor
- Updated instantiation logic in `mock_multi_agent.py` to restore runtime functionality
- Implemented `mock_stock_server.py` to handle stock-related computations
- Added a stock analysis agent in `mock_multi_agent.py` to process financial queries
- Updated `.replit` configuration to support new server integration
- Updated `system_prompt` in `mock_multi_agent.py` to guide user expectations
- Clearly stated supported operations and how agent should respond to capability questions
- Updated system prompt in `mock_multi_agent.py` to reflect only supported tools
- Added error handling in `mock_math_server.py` to reject unsupported operations
- Ensured agent behavior stays within defined context and MCP protocol limits
- Modified `mock_multi_agent.py` to avoid duplicate responses from multiple calculators
- Integrated logic using `agent.py` and `mcp_integration.py` for proper agent-tool mapping
- Updated output formatting and response control for clearer user experience
- Set `gpt-4o-mini` explicitly as model to ensure consistent responses
- Fixed agent configuration and response parsing in `mock_multi_agent.py`
- Updated `mock_math_server.py` and `.replit` config for accurate debugging and logging
- Created `mock_math_server.py` to simulate MCP server behavior
- Developed `mock_multi_agent.py` to orchestrate agent–server interaction
- Added `mock_integration_test.py` to validate end-to-end data flow
- Ensured user input → server request → agent processing → user output pipeline
Pavan Kumar
DP37