Assistant generated file changes:
- examples/mcp_example/mock_multi_agent.py: Update agent capabilities response
---
User prompt:
When asked for what the agent can do, it responds two things, but it doesnt specify which agent will do which thing Include the agent name with the operations into it
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_stock_server.py: Fix FastMCP server initialization parameters
---
User prompt:
imnnot getting any putput now pfr the dotocaget fix that
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_stock_server.py: Fix FastMCP run parameters
---
User prompt:
When asking for the price, I am not getting it
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Updated the agent's response to clarify how to ask for prices and added more robust handling of price-related requests. Specifically, modified `mock_multi_agent.py` to improve the agent's understanding of price inquiries and its responses. The `.replit` file was also updated to rename the run button to "Run MCP Demo".
Replit-Commit-Author: Assistant
Assistant generated file changes:
- examples/mcp_example/mock_stock_server.py: Fix FastMCP server configuration
- examples/mcp_example/presentation_script.md: Add presentation script
- .replit: Updated app configuration
---
User prompt:
Give me updated presentation that how I could show that mcp integration has been done successfully into the ancient architecture and with examples of mock multi agent mock math server, mock stock server and how the local client side implementation and the server side implementation has been done I want to explain them the whole thing Give me a script step by step as a presentation
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_stock_server.py: Update to use FastMCP
---
User prompt:
i see the severs use fast mcp insed of mcp but the agets use mcp howthis is working ?
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_multi_agent.py: Simplify agent output format
---
User prompt:
id there are two agents then it sahd towsitlap the aprlicutlatedt adn i donrwant to see the agent disctiosn in every reeult ""
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_multi_agent.py: Clean up response display
---
User prompt:
why im getthin the th all the thisnds what the ussedshoudl get only that thisnthe usereshoudl get whr its reuntet esoleutjoin whic is not necessaly "
Multi-Agent Math System
Enter 'exit' to quit
Enter a math problem: add 3 and235
╭────────────────────────── Agent Name Calculator [Max Loops: 1 ] ──────────────────────────╮
│ Calculator: To add 3 and 235, you can perform the calculation: │
│ │
│ 3 + 235 = 238. │
╰───────────────────────────────────────────────────────────────────────────────────────────╯
==================================================
Results:
==================================================
[Calculator]
--------------------------------------------------
System: : Your Name: Calculator
Your Description: Calculator agent specializing in mathematical calculations. For Calculator: use add, multiply, divide operations. For Stock Analyst: use moving averages and percentage change calculations.
You are Calculator, a math processing agent. You have access to these mathematical operations ONLY: addition, multiplication, and division. Only suggest calculations using these available tools. Do not attempt to solve problems requiring other operations like percentages, square roots, or advanced math. When users ask about capabilities, list only the basic operations you can perform.
Human:: add 3 and235
Calculator: To add 3 and 235, you can perform the calculation:
3 + 235 = 238.
==================================================
Enter a math problem: "
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/mock_multi_agent.py: Update agent processing logic to handle only relevant tasks, Update results display to only show relevant responses
---
User prompt:
im facing the issue that whaen i send the agetn one speroce task it is send to tbothe agetn tand both the gets ater retuneitnthe the answers and udpate ti fix this and udpate it only it shoudl be repsonced by the rools or agetreas which is relvent to them
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Assistant generated file changes:
- examples/mcp_example/demo_presentation.py: Create demo script
---
User prompt:
I would be presenting this to my manager. So give me what kind of files that I need to show him, and what kind of step by step presentations that I need to show him that there is a successful MCP integration into the client or agent and the whole workflow is working properly. I need to satisfy him
Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
- 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
- Fixed `math_server.py` to support clean server initialization
- Updated `multi_server_test.py` to validate single agent interactions with multiple MCP servers
- Fixed port configuration in `math_server.py` to ensure proper server startup
- Updated response handling in `multi_server_test.py` to resolve missing outputs during testing
- Adjusted `math_server.py` and `calc_server.py` to support many-to-many agent-server interactions
- Resolved config inconsistencies causing agents to fail output delivery
- Ensured each agent can access appropriate tools from multiple MCP servers
- Resolved broken or missing import statements in `math_server.py` and `calc_server.py`
- Updated server initialization to ensure proper startup and output delivery
- Corrected initialization issues in `math_server.py` and `calc_server.py`
- Improved response formatting and delivery in `multi_server_test.py`
- Resolved issue where agent output showed raw stream wrapper instead of actual response
- Improved clarity and readability of agent responses in `multi_server_test.py`
- Added a dedicated function to format multi-agent outputs consistently
- Updated all agents in `multi_server_test.py` to explicitly define model name
- Eliminated LiteLLM fallback warnings during runtime
- Ensured proper agent responses in multi-agent MCP test environment
- Resolved model selection warnings by specifying 'gpt-4o-mini'
- Ensured agents explicitly define model name to avoid default fallbacks
- Improves clarity and consistency in agent–MCP server communication
- Created `multi_server_test.py` to test coordination across agents and servers
- Added `calc_server.py` for handling computation requests
- Referenced swarms-rs Rust architecture for Python-based design structure
- Created proper MCP-compatible `math_server.py`
- Set up `test_integration.py` with multi-agent system structure
- Updated `.replit` config for seamless client-server testing
- Updated `math_server.py` and `test_integration.py` to explicitly use 'gpt-4o-mini'
- Ensures consistent model configuration across test and runtime environments
Pavan Kumar
DP37