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node v22.22 · mcp ready

███████╗██████╗ ███████╗ ██████╗████████╗███████╗██████╗ ██╔════╝██╔══██╗██╔════╝██╔════╝╚══██╔══╝██╔════╝██╔══██╗ ███████╗██████╔╝█████╗ ██║ ██║ █████╗ ██████╔╝ ╚════██║██╔═══╝ ██╔══╝ ██║ ██║ ██╔══╝ ██╔══██╗ ███████║██║ ███████╗╚██████╗ ██║ ███████╗██║ ██║ ╚══════╝╚═╝ ╚══════╝ ╚═════╝ ╚═╝ ╚══════╝╚═╝ ╚═╝ v1.4.0 — Codebase Narrator & MCP Server Engine (@purplegumdropz/specter) Type "help" to view available commands, or try "specter explain".

Story · how this shipped

The brief

Developers building AI agents have zero visibility into execution flow, costs, and errors. Existing tools like LangSmith cost $29-299/mo and send data to external servers.

The build

Built local-first observability platform with Rust backend (Axum + SQLite) and React 19 frontend. Implemented semantic caching proxy (30-50% cost reduction), fire-and-forget tracing (zero latency), DAG visualization, and MCP server for AI assistant integration.

What shipped

29 tests passing (0.11s runtime). 808KB optimized UI bundle. Zero-cost local-first architecture. Semantic caching reduces LLM costs 30-50%. MCP integration enables natural language trace queries. 9.5/10 documentation score.

Signals

Scale & impact

29 passing

Tests

Rust + Axum + SQLite

Stack

Yes

MCP Tools

Engine room

At a glance

Tests

Inventory

Stack & signals

RustAxumSQLiteReact 19TypeScriptViteTailwindPython SDK

Let's talk

Tell me what you're building

If you need someone who can own UI, systems, and AI integration without losing the plot, I'm listening. Contract, advisory, or full-time: we'll find the right shape.

Start a conversation See more projects

Signal = how many tags a project shares with this one.

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