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4 Commits (07f4c65bdea557078e74bd38363f71dc7b5431d0)
| Author | SHA1 | Message | Date |
|---|---|---|---|
Pavan Kumar
|
f69682f31b |
chore: add detailed logging to MCP server for end-to-end data flow visibility
- Instrumented `mock_math_server.py` to log incoming agent requests and tool responses - Ensured logs clarify the MCP protocol: agent → MCP server → tool → response → agent - Supports debugging and compliance with Model Context Protocol (MCP) flow |
3 months ago |
|
Pavan Kumar
|
40cd5248d8 |
fix: align math server tools and agent prompt with available capabilities
- 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 |
3 months ago |
|
Pavan Kumar
|
3899a22c97 |
fix: correct MCP agent response handling and model configuration
- 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 |
3 months ago |
|
Pavan Kumar
|
a8ad884d27 |
feat: implement mock MCP server and multi-agent system with full integration flow
- 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 |
3 months ago |