ConversationalBot_AgenticAI_LangGraph_MCP

• Sample data is created in sqlite(data can be viewed using sqlite-web - https://github.com/coleifer/sqlite-web), to acces the data, FastAPI is used(scripts and requirements.txt is kept in CreateSQLDB_FastAPIGetDB.zip)
• Streamlit based Conversational Bot to access the above data using MCP Client(using langchain_mcp_adapters) with LangGraph's Prebuilt Supervisor Agents & Sequential flow-MCP Server connection with SSE, and JWT(scripts are in MCPClient_MCPServer_LangGraph_Scripts.zip)
• Instead of SSE connection, streamable-http can be used as well
• Conversational Bot's screenshot is available in PDF format
• MCP Servers can be directly run as "python.exe mcpsfilename.py" and to run MCP Client in this case run the streamlit python file using "python.exe -m streamlit run streamlitpythonfile.py" because streamlit python file internally calls the MCP Client function