dspy_jira_mcp_chat

# JIRA MCP Chatbot A conversational AI assistant built with DSPy and Streamlit that helps users query and interact with JIRA data through natural language. ## Project Overview  This project implements an AI-powered airbnb assistant that can answer questions, find tickets, and provide insights about airbnb data through natural language conversations. The system uses: - **DSPy**: A framework for programmatically controlling language models - **Streamlit**: For building the interactive web interface - **FastAPI**: For the backend API server - **MCP (Model Control Protocol)**: For managing the communication with various tool servers [DSPy Unofficial](https://github.com/ThanabordeeN/dspy-mcp-intregration.git) ## Architecture The project consists of two main components: ### 1. Backend (FastAPI Server) - Handles communication with DSPy and the language model - Manages MCP server connections to JIRA through the Atlassian MCP server - Implements the ReAct agent for reasoning and tool use - Maintains conversation history ### 2. Frontend (Streamlit App) - Provides a chat interface for users - Sends queries to the backend - Displays responses from the AI assistant ## Setup Instructions ### Prerequisites - Python 3.9+ - API key for Google Gemini (or other compatible LLM) - JIRA account with API access token ### Installation 1. Clone this repository: ``` git clone <repository-url> cd jira_mcp ``` 2. Install dependencies: ``` pip install -r requirements.txt ``` 3. Set up environment variables: ``` export GOOGLE_API_KEY=your_api_key_here ``` ### Configuration The MCP server configuration is located in `backend/servers_config.json`. This file defines the JIRA connection details including URL, username, and token. You can use the `servers_config.example.json` file as a template. ## Running the Application 0. Install DSPy (MCP Version - Unofficial): ```bash git clone https://github.com/ThanabordeeN/dspy-mcp-intregration.git && cd dspy-mcp-intregration && pip install . ``` 1. Start the backend server: ``` cd backend uvicorn main:app --host 0.0.0.0 --port 8001 --reload ``` 2. In a separate terminal, start the Streamlit frontend: ``` streamlit run main.py ``` 3. Open a web browser and navigate to `http://localhost:8501` ## Usage 1. Enter your JIRA-related questions in the chat input 2. The assistant will process your query, potentially using JIRA tools from the MCP server 3. Review the response in the chat interface ## Example Queries - "Show me all critical bugs assigned to me" - "What's the status of the authentication project?" - "List open tickets in the frontend component" - "Who's working on the most tickets this sprint?" ## Project Structure ``` jira_mcp/ ├── README.md # This documentation ├── main.py # Streamlit frontend ├── .gitignore # Git ignore file ├── backend/ │ ├── main.py # FastAPI backend server │ ├── servers_config.json # MCP server configuration │ └── servers_config.example.json # Example config template └── requirements.txt # Project dependencies (not yet included) ``` ## License MIT License ## Contributing Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.