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Atlas

Local MCP server for codebase ingestion, AI-powered query, impact analysis, and edge-case detection.

Atlas gives AI coding assistants (Claude, Cursor, Windsurf, VS Code) a structured knowledge base of your codebase — so they make 1 tool call instead of 15.

Without Atlas: Claude opens 7 files, runs 5 greps, makes 15 tool calls to understand context
With Atlas:    1 call to atlas_query. Done.

Measured 93% reduction in tool-call overhead per coding task.


How it works

Atlas runs as a local MCP server. It indexes your codebase into a local Meilisearch instance, then exposes 5 tools your AI client calls over stdio — no cloud, no API key, no data leaving your machine.

The five tools

Tool What it does
atlas_ingest Crawl a codebase, parse 18 languages, build a call graph, detect cross-language bridges, write to local index
atlas_query Natural language question → BiLSTM query model → structured results
atlas_impact Given a list of functions, find every function that would break if they change
atlas_edge_check Full safety pass: impact analysis + verification layer over proposed code change (Pro)
atlas_status Check if a project is indexed and how many documents are in the index

Supported languages

Python, JavaScript, TypeScript, Go, Rust, Java, C#, C, C++, Ruby, PHP, Swift, Kotlin, Scala, Lua, Elixir, Dart, Zig

Cross-language bridge detection

Atlas detects relationships that span language boundaries:

  • HTTP/REST route matching between frontend and backend
  • Shared environment variable references
  • Shared config file references
  • Database schema/table bridges across ORMs
  • Shared type/interface definitions

Installation

pip install atlas-mcp
atlas init

atlas init will:

  1. Download and start Meilisearch locally
  2. Crawl and index your codebase
  3. Write the MCP config to .claude/settings.json

MCP config (Claude Desktop / VS Code)

{
  "mcpServers": {
    "atlas": {
      "command": "python",
      "args": ["-m", "atlas.server"],
      "env": { "ATLAS_KEY": "your-licence-key" }
    }
  }
}

Pricing

Tier Price Projects Languages Query model
Free $0 1 Python only Raw keyword search
Pro $19/month Unlimited All 18 Trained BiLSTM
Team $79/seat/month Unlimited All 18 Trained BiLSTM + shared indexes
Enterprise $149/seat/month Unlimited All 18 Full suite + SSO + SLA

Get your licence key at hornsa.com/atlas


Open-core model

The ingestion pipeline, MCP server, call graph walker, and model architecture are open source (Apache 2.0).

The training pipeline, trained model weights, and verifier bridge are proprietary — distributed to paid licence holders only.

Component Licence
atlas/ingest/ Apache 2.0
atlas/server.py Apache 2.0
atlas/edge/impact.py Apache 2.0
atlas/query/net.py Apache 2.0
atlas/cli.py Apache 2.0
Training pipeline Proprietary
Trained weights Proprietary
Verifier bridge Proprietary

Requirements

  • Python 3.11+
  • 4 GB RAM (8 GB recommended for large codebases)
  • 2 GB disk (Meilisearch + weights)
  • Internet required at install and for daily licence token refresh

Support


Built by Horn Software Architects

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