artk0de/tearags-mcp
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The Codebase Intelligence layer for AI coding agents. Semantic indexing, graph navigation, and repository intelligence
개요
Codebase Intelligence layer for AI coding agents Trajectory Enrichment-Aware RAG · served over MCP · 100% local TeaRAGs is a your agent queries over MCP. It indexes the repository on your machine into five layers — three that read the code and two that judge its interfaces: - 🔍 — semantic and hybrid search over AST-aware chunks - 🕸️ — callers, callees, fan-in, transitive impact - 🧬 — churn, bug-fix rate, ownership, age - 🏛️ — dependency direction, leaking facades, files that change together with no edge between them - 🔤 — the naming vocabulary, inferred from the call graph, and a verdict on every new name The first three layers and why an agent needs all of them at once are laid out in Codebase Intelligence для агента (Habr, in Russian). TeaRAGs also ships agent skills that know which layer a task needs. The agent stops guessing which code is safe to copy, what is critical, and what a change will break — it reads the dossier instead.
README
원문 README의 일부입니다. 원문 보기.
TeaRAGs 🦖🍵
Codebase Intelligence layer for AI coding agents Trajectory Enrichment-Aware RAG · served over MCP · 100% local
Your coding agent copies the first code it finds — not the right one.
TeaRAGs is a Codebase Intelligence layer your agent queries over MCP. It indexes the repository on your machine into five layers — three that read the code and two that judge its interfaces:
- 🔍 What it does — semantic and hybrid search over AST-aware chunks
- 🕸️ How it is connected — callers, callees, fan-in, transitive impact
- 🧬 How it has lived — churn, bug-fix rate, ownership, age
- 🏛️ Whether it is laid out right — dependency direction, leaking facades, files that change together with no edge between them
- 🔤 What the project calls things — the naming vocabulary, inferred from the call graph, and a verdict on every new name
The first three layers and why an agent needs all of them at once are laid out in Codebase Intelligence для агента (Habr, in Russian).
TeaRAGs also ships agent skills that know which layer a task needs. The agent stops guessing which code is safe to copy, what is critical, and what a change will break — it reads the dossier instead.
📖 Documentation · 🏁 15-minute quickstart · 🧠 Core concepts
👀 See It
Three questions an agent asks before touching code, answered by TeaRAGs on its own repository. Every number below is a real response, trimmed.
1. “Find retry logic I can reuse”
설치
This server does not publish a one-line install command.
Open the repository installation guide MCP 초보자라면? mcpskill.org 가이드부터 시작하세요 →설정
{
"mcpServers": {
"tea-rags": {
"command": "tea-rags",
"args": ["server"]
}
}
}