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- Updated config.py to include new settings for Watchdog, Slack channels, and improved error handling. - Introduced inspector_runner.py to facilitate running the MCP Inspector. - Refactored query_kb.py for better error handling and prompt management. - Added mifos_tools.py with various utility functions for Jira, GitHub, and Slack integrations. - Implemented prompts for summarizing GitHub activity, generating JQL, and synthesizing knowledge base responses.
- Created a new .env.example file for environment variable configuration. - Refactored agent_start.py to streamline imports and improve webhook handling. - Updated rag_agent.py to fix import paths for RetrievalQA. - Refined mifos_tools.py by initializing FastMCP and restructuring Jira and GitHub client functions. - Enhanced error handling and logging across various functions. - Added tool wrappers for Jira context, Mifos documentation queries, GitHub details, CI checks, and smart search.
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I have successfully upgraded my existing pipeline into an intelligent watchdog that doesn't just trigger—it understands.
Key Wins
• Deep Jira Context: The agent now detects ticket keys (e.g., WEB-95) in PR titles and instantly fetches live status, assignee, and requirements from my Jira server.
Technical Note: I implemented smart truncation logic to handle large Jira descriptions. This ensures I stay within Slack's 3,000-character block limit, preventing notification crashes while preserving key context.
• RAG-Powered Guidance: Instead of generic checks, the agent queries my Pinecone Knowledge Base. In my "GLIM Moratorium" test, it successfully provided specific architectural advice for the Fineract engine.
• Unified Reporting: All insights—Jira context, RAG advice, and CI status—are now synthesized into a single, structured Slack report.
MCP Inspector Verification
I went beyond functional testing by validating our architecture with the MCP Inspector. I successfully loaded and executed my core tools directly within the Inspector environment :
tool_jira_context (Jira Integration)
tool_knowledge_base (RAG/Vector DB)
tool_ci_check (CI Status Check)
tool_github_details (PR Metadata & Retrieval)