podqapath

An Agentic Release Auditor for Pod-Based QA Teams.

PodQApath uses the Model Context Protocol (MCP) to map Jira custom fields to specific QA pods, providing 1:1 traceability between requirements and auto-deployed environments.

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• Pod-Aware Traceability — Automatically maps Jira custom fields to specific Pods and assigned QA members.
• Environment Auditing — Correlates merged Pull Requests with Jira tickets to verify what is actually deployed in the QA environment.
• Agentic Analytics — An integrated AI Assistant (powered by Claude 3.5) that analyzes code churn and requirement gaps in real-time.
• Hybrid Data Sourcing — Switch between Live API mode and Local CSV Audit mode for restricted corporate environments.

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| Layer | Technology | |---|---| | UI | Streamlit (Python) | | AI Protocol | Model Context Protocol (MCP) | | Logic | Python 3.11+ | | AI SDK | Anthropic SDK | | Integrations | Jira Software, GitHub (via MCP) |

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git clone https://github.com/teddyski/podqapath.git
cd podqapath

Copy .env.example to .env and fill in your credentials:

cp .env.example .env

Required keys:

• ANTHROPIC_API_KEY — Your Anthropic API key
• JIRA_BASE_URL — Your Jira instance URL
• JIRA_EMAIL — Your Jira account email
• JIRA_API_TOKEN — Your Jira API token
• GITHUB_TOKEN — Your GitHub personal access token

pip install -r requirements.txt

streamlit run app.py

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By centralizing deployment data and ticket status into a single command center, PodQApath reduces triage time by up to 40% and eliminates the "Collision Risk" common in shared QA environments.

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MIT License — free for personal and commercial use. See LICENSE for details.