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Capture, scale, and enforce technical decisions across engineering teams.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "ai.packmind/mcp-server" MCP server from askskill: Run: claude mcp add --transport http 'ai-packmind-mcp-server' 'https://app.packmind.ai/mcp'
Help me document this technical decision about splitting a monolith into microservices, including context, alternatives, final choice, trade-offs, risks, and follow-up actions.
A structured technical decision record that the team can share, reuse, and track.
Based on our code review rules, branching strategy, and dependency management principles, summarize them into actionable engineering standards and identify which rules should be enforced automatically.
A clear list of engineering standards with recommendations for automated enforcement or review.
Check whether this implementation plan aligns with our existing technical decisions, especially logging standards, API design conventions, and security requirements, and list any deviations.
An alignment review showing compliant areas, deviations, and suggested improvements.
Connect AI apps to a shared knowledge graph for consistent retrieval and reasoning.
Give AI coding agents filesystem, Git, database, and compute tools via MCP.
Access and manage engineering docs with traceable support for requirements, tests, and impact analysis.
Give AI coding agents persistent code memory while cutting token usage dramatically.
Secure file and directory operations for autonomous AI development workflows.
Give AI agents persistent memory and personal knowledge graph capabilities.