Qartez
Code Intelligence MCP for AI Agents
Qartez gives AI coding assistants a real understanding of a codebase. It is a Rust MCP (Model Context Protocol) server that builds a language-aware index and replaces naive file search with structured tools: jump to any symbol, trace call hierarchies, measure the blast radius of a change before editing, and run guarded refactors. The core server is source-available: free for individuals and small teams, with a commercial licence for larger companies and a hosted offering at qartez.dev.
Highlights
How it Works
Install in One Line
A single command installs the server and auto-configures the MCP-capable IDEs and agents it detects.
Auto-Index on Open
Open a project and Qartez parses it into a local graph - no manual indexing step.
Agent Queries the Graph
Your assistant calls purpose-built tools for navigation, impact, and analysis instead of grepping files.
Stay in Sync
A file watcher re-indexes changed files in the background, so the graph stays fresh as you edit.
Features
Pre-Computed Code Graph
Your agent queries a prebuilt graph of symbols, imports, and call edges instead of re-reading files, so it answers with a fraction of the tokens.
Symbol-Level Navigation
Jump to definitions, references, and call hierarchies across the whole codebase from the index.
Impact Analysis
Measure the blast radius of a change before editing a load-bearing file - direct importers, transitive dependents, and co-change partners.
Modification Guard
Blocks edits to high-impact files until the agent reviews the blast radius first, so it stops making blind changes.
Guarded Refactors
Rename symbols, move them between files, and rewrite imports across the repo with safety checks that catch breakage early.
Local and Private
A single Rust binary parses your code into a local index - no vector database, no cloud, nothing leaves your machine.
Use Cases
Token-Efficient Agents
Cut the cost of every AI coding session by routing questions through the index instead of file scans.
Safe Refactoring
Know exactly what breaks before touching a critical file in a large codebase.
Onboarding a Codebase
Get an importance-ranked reading list and a structural map of any unfamiliar repo.
Pre-Merge Review
See the combined blast radius and co-change risk of a whole git diff in a single call.
Who it's For
Developers and teams using AI coding agents who want faster, cheaper, and safer code intelligence on large or unfamiliar codebases.
Ready to try Qartez? See it in action.
Visit QartezFAQ
It is source-available rather than open source in the OSI sense. The core server's full source is published and linked from this page, and it is free to use for individuals and small teams; larger companies need a commercial licence. A hosted offering is available at qartez.dev.
No. Qartez is local-first - a single Rust binary parses your code into a local index. There is no vector database, no cloud, and nothing leaves your machine.
It gives the agent a pre-computed code graph of symbols, imports, and call edges, plus 40+ MCP tools for symbol navigation, call hierarchies, and impact analysis - so it answers with a fraction of the tokens instead of re-reading files.
It measures the blast radius of a change before you edit a load-bearing file - direct importers, transitive dependents, and co-change partners - and a modification guard blocks edits to high-impact files until the agent reviews that radius first.
A single command installs the server and auto-configures the MCP-capable IDEs and agents it detects. When you open a project, Qartez parses it into a local graph with no manual indexing step.
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