What is Dspy Jira Mcp Chat

dspy_jira_mcp_chat is a conversational AI assistant designed to help users interact with JIRA data using natural language. It leverages DSPy for language model control and Streamlit for a user-friendly interface.

Use cases

Use cases include answering questions about JIRA tickets, retrieving specific ticket information, providing insights on project statuses, and facilitating communication between team members regarding task management.

How to use

To use dspy_jira_mcp_chat, clone the repository, install the required dependencies, set up your environment variables, configure the JIRA connection details, and run the application. Users can then interact with the chatbot through the Streamlit interface.

Key features

Key features include natural language processing for querying JIRA data, integration with FastAPI for backend services, conversation history management, and a user-friendly chat interface built with Streamlit.

Where to use

dspy_jira_mcp_chat can be used in project management, software development, and any organization that utilizes JIRA for tracking tasks and issues, enhancing productivity through conversational interfaces.

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

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):

   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.