Agentic Engineering Toolkit
AvailableMCP servers, skills, and RAG pipelines for AI-accelerated development
A suite of production-tested tools that let AI agents operate autonomously across codebases: MCP servers for domain knowledge, structured skill systems, and multi-codebase RAG with pgvector.
This toolkit is what I use every day to build software faster. It includes MCP servers in Python and Java that serve multi-codebase domain knowledge via RAG with pgvector embeddings. Structured skill and context file architectures (CLAUDE.md, SKILL.md, AGENT.md) define boundaries and capabilities for autonomous coding agents.
The impact is measurable: at BluePallet, non-trivial feature development dropped from approximately 4 weeks to 2 weeks on production codebases. Code review turnaround went from days to under 15 minutes.
Also includes multi-agent delegation patterns for parallel work across isolated project workspaces, and an internal AI support agent for production triage and diagnostics.
Key Features
- MCP servers in Python and Java serving multi-codebase domain knowledge
- Structured skill/context file systems for autonomous agent operation
- Prompt architectures for feature implementation, code review, and automation
- Multi-agent delegation patterns for parallel work across projects
- Internal AI support agent for production triage and diagnostics
- RAG pipeline with pgvector embeddings for code and documentation
Built With
Interested in this solution?
I can help you deploy, customize, or build something similar for your specific needs.