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2025Solo
Custom Agent Core with MCP
LLM core with a plugin execution layer for a developer assistant: hot reload, tool chains, and explicit context handoff.
Hot-reload
Context handover
CLI + API
Execution core
Plugins can evolve without resetting the whole assistant.
This is a durable execution layer, not a one-off demo.
1Plugin lifecycle is separated from core concerns
2Hot-reload keeps iteration speed high
3Cascading tool calls use explicit context handoff
AI Tooling Engineer
PythonFastAPIMCPTool callingLLM APIs
Problem
Once an assistant gets more capable, plugins become hard to evolve and orchestration gets brittle.
Solution
Built an EnhancedMCP core: FastAPI server, plugin lifecycle management, hot reload, cascading tool calls, and a CLI client with execution history.
Impact
The result is a reusable core that can support new workflows and tools without a full rewrite.
What I built
- Implemented plugin hot reload without restarting the core process.
- Built explicit context handoff between chained tools.
- Separated core runtime responsibilities from plugin responsibilities to keep the platform maintainable.
What this proved
- Architecture matters more than model count in AI tooling.
- Developer trust comes from predictable execution behavior.
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