Contextatlas MCP server

ContextAtlas

Stop watching Claude burn tokens grepping for context it can't possibly find.

ContextAtlas turns your codebase into a single-call context bundle for Claude Code — fusing LSP-grade structure, architectural intent from your Architectural Decision Records (ADRs), git history, and test associations. Measured 45-72% token reduction with zero quality regression across benchmark axes on architectural prompts across the hono / httpx / cobra benchmark suite.

Quick start → · Benchmark results → · Why not graph-based? → · Architecture → · ADRs →

ContextAtlas ships two equivalent paths — CLI and Claude Code Skills — both producing the same atlas.json. See Quick Start for setup.

The Problem

Claude Code currently learns your codebase by brute force. Every session starts fresh. Every "where is X?" triggers multiple grep calls. Every "what depends on Y?" is another flurry of file reads. On a mid-sized codebase, answering a single architectural question can consume 40+ tool calls and 100,000+ tokens before Claude has enough context to reason well.

Worse: the architectural intent that governs your code — the ADRs, the design decisions, the "we did it this way because" — is invisible to Claude. The rule that OrderProcessor must be idempotent lives in docs/adr/. When Claude proposes a change, it has no way to know that constraint exists.

Yesterday's understanding doesn't carry to today. Every conversation starts from zero. Your ADRs, your commit history, your test coverage — none of it is on the agent's table.

What if expensive understanding happened once, at index time, and every query became a dictionary lookup?

That's ContextAtlas.

What ContextAtlas Is

ContextAtlas is an MCP server that gives Claude Code a curated atlas of your codebase — fusing LSP-grade structural precision with architectural intent extracted from your ADRs, docs, and git history, delivered to Claude in single-call context bundles.

Every bundle Claude receives combines four independent signals about a symbol:

types, diagnostics. Compiler-grade precision.

1. Structural data from the language server — definition, references,

structured claims extracted by Opus 4.7 at index time, keyed to specific code symbols.

1. Architectural intent from your ADRs, READMEs, and design docs —

hot/cold indicators, co-change patterns.

1. Historical context from git — recent commits touching the symbol,

coverage lives.

1. Test associations — which tests reference the symbol, where

One MCP call returns all four, fused. No ADRs in your repo yet? You still get LSP + git + tests in one call instead of fifteen — a meaningful baseline improvement. Add ADRs and the bundles get richer. The architecture is designed so any subset of signals produces value.

Given an ADR stating that OrderProcessor must be idempotent, a call to getsymbolcontext("OrderProcessor") returns:

Shortened. The full README is on GitHub.