Qartez MCP X-ray vision for your codebase - built for AI agents, not humans. The first code-intelligence server designed from day one to be consumed by language models , not read by people.
개요
Qartez MCP X-ray vision for your codebase - built for AI agents, not humans. The first code-intelligence server designed from day one to be consumed by language models , not read by people.
README
Qartez MCP
X-ray vision for your codebase - built for AI agents, not humans.
The first code-intelligence server designed from day one to be
consumed by language models, not read by people. Cuts AI token usage by ~94%.
Quickstart ·
43 Tools ·
Guard ·
Benchmarks ·
Comparison ·
37 Languages ·
CLI ·
Contributing ·
Security ·
Changelog
Why this exists
grep, find, cat, and ls were invented in the 1970s for humans reading one file at a time in a terminal. Half a century later, your AI assistant is still using them - scanning files byte by byte, re-reading the same directories on every question, guessing at what matters, and burning your tokens on work the tools were never designed to do.
Qartez is a different species of tooling. It is not a wrapper around grep. It is a pre-computed knowledge graph of your repository - symbols, imports, call edges, blast radii, PageRank, git co-change, cyclomatic complexity - served to any LLM through the Model Context Protocol. The agent stops reading your codebase and starts querying it.
Think of it as the first purpose-built sensory organ for coding agents. Grep sees one line at a time. Qartez sees the entire shape of the codebase in one glance.
Every time your AI assistant touches code, three expensive things happen:
1. It reads the same files over and over. No memory of the repo. Every question starts from scratch. You pay for every token - again and again.
2. It can’t see what will break. Your assistant edits utils.ts without knowing 14 other files import it. You find out in CI. Or in production.
3. It wastes tokens finding things. “Where is handleRequest defined?” turns into Grep across 200 files, Read on 5 candidates, and 1,600 tokens burned before it finds the answer. Qartez answers that in 50 tokens.
The fix isn’t a smarter model. It’s a smarter index.
Quickstart
Platform support: macOS 13+, Ubuntu 22.04+ (and other modern Linux, gnu or musl), Windows (native PowerShell 5.1+/7+) and WSL 2. Architectures: x86_64 and arm64. Rust MSRV is 1.88 - only needed for unsupported platforms or the --from-source escape hatch.
Install (recommended)
Pick the one-liner for your operating system. Both commands do the same thing: download a pre-built binary, verify its SHA-256 against the release’s SHA256SUMS, install the three binaries (qartez, qartez-guard, qartez-setup), and launch qartez-setup in non-interactive mode to configure every MCP-capable IDE it detects (including the modification-guard hooks for Claude Code).
macOS / Linux / WSL 2 - bash installer, binaries land in ~/.local/bin/:
curl -sSfL https://qartez.dev/install | sh
Windows (native PowerShell 5.1+/7+) - PowerShell installer, binaries land in %LOCALAPPDATA%\Programs\qartez\:
powershell -ExecutionPolicy Bypass -c "iwr https://raw.githubusercontent.com/kuberstar/qartez-mcp/main/install.ps1 -useb | iex"
Unsupported platforms (e.g. linux-musl arm64 without a published artifact) fall back to a local cargo build automatically; pass --from-source (bash) or -FromSource (PowerShell) to force that path. Rust MSRV 1.88 is only required for that fallback.
Open any project in your IDE - Qartez indexes it automatically on session start. No manual step needed. The file watcher keeps the index fresh as you edit.
What Qartez does
Qartez builds a knowledge graph of your codebase - once - and serves it to any AI assistant through MCP. Instead of scanning files from scratch on every question, your assistant queries a pre-computed index that knows:
- Which files matter most (PageRank on the import graph)
- What breaks if you change a file (blast radius analysis)
- Which files always change together (git co-change mining)
- Which functions are the most dangerous to touch (cyclomatic complexity x coupling x churn)
- Where every symbol is defined, who uses it, and who calls it
- Which blocks of code are duplicated (structural AST shape hashing)
- Which architecture boundaries the imports are violating
- What types implement a trait/interface, and vice versa
The result: your AI works faster, uses fewer tokens, refactors safely, and stops making blind changes to load-bearing files.
Before and after
| Task | Without Qartez | With Qartez |
|---|---|---|
“Where is QartezServer defined?” |
Grep 200 files, Read candidates. 1,490 tokens. | qartez_find. 52 tokens. |
“What breaks if I change storage/read.rs?” |
BFS grep from imports, depth 2. 9,243 tokens. | qartez_impact: direct + transitive importers + co-change. 352 tokens. |
“Outline src/server/mod.rs (96 symbols)” |
Read full 300KB file. 77,843 tokens. | qartez_outline with signatures. 3,009 tokens. |
| “Find all dead exports” | Impossible without tooling. | qartez_unused: pre-materialized, instant. 468 tokens. |
| “Which functions are the riskiest to refactor?” | Nothing to query. | qartez_hotspots: complexity x PageRank x churn. |
The 43 tools
Think of these as the standard library for AI code understanding. Each one replaces a multi-step human workflow with a single, token-efficient call the agent can reason about.
Tools are organized into tiers with progressive disclosure. Core tools are always available. Additional tiers can be unlocked on demand via qartez_tools enable: ["analysis"] (or "all").
Core (always available)
| Tool | What it does |
|---|---|
qartez_map |
Start here. Project skeleton ranked by importance. PageRank, exports, blast radii. Boost by files or terms to focus on what you’re working on. |
qartez_find |
Jump to a symbol definition by exact name. File, line range, signature, visibility. No scanning. |
qartez_grep |
FTS5 search across indexed symbols. Prefix matching, regex fallback, optional body search. |
qartez_read |
Read one or more symbols’ source code with line numbers. No file scanning. Jumps directly to the symbol. |
qartez_outline |
Table of contents for any file: every symbol grouped by kind, with signatures. |
qartez_impact |
Call before editing any important file. Shows direct importers, transitive dependents, and co-change partners. Everything that could break. |
qartez_deps |
Dependency graph for a file: what it imports, what imports it. |
qartez_stats |
Codebase dashboard: files, symbols, edges by language, most-connected files. |
Analysis (unlock via qartez_tools)
| Tool | What it does |
|---|---|
qartez_refs |
Trace every usage of a symbol across the codebase, with optional transitive chains. |
qartez_calls |
Call hierarchy: who calls this function, and what does it call. |
qartez_cochange |
Files that historically change together in git. Logical coupling invisible to the import graph. |
qartez_context |
Smart context builder: given files you plan to modify, returns the optimal set of related files to read first. |
qartez_unused |
Dead-code finder: exported symbols with zero importers, pre-materialized at index time. |
qartez_diff_impact |
Batch impact for a git diff range. Pass a revspec like main..HEAD to get changed files with PageRank, union blast radius, convergence points, and co-change omissions. One call replaces N calls to qartez_impact + qartez_cochange. |
qartez_hotspots |
The refactor radar. Ranks files and functions by hotspot score = cyclomatic complexity x PageRank x (1 + churn). Points straight at the highest-risk code in the repo. |
qartez_clones |
Structural code-clone detection via AST shape hashing (identifiers, literals, and comments are normalized away). Finds duplicate logic the human reviewer would never spot. |
qartez_boundaries |
Architecture-boundary enforcement. Declare “these modules may not import those” in .qartez/boundaries.toml and get every violating edge back. suggest=true seeds a starter config from the Leiden clustering. |
qartez_hierarchy |
Type hierarchy queries: find all types implementing a trait/interface, or all traits/interfaces a type implements. Works across Rust, TypeScript, Java, Python, and Go. |
qartez_trend |
Complexity trend over git history: tracks how a function’s cyclomatic complexity evolved commit by commit. Flags functions that are GROWING, STABLE, or SHRINKING. |
qartez_security |
Security scanner with 13 built-in rules. Regex-based pattern matching scored by PageRank to prioritize high-impact files. Custom rules via .qartez/security.toml. Filters by severity (low/medium/high/critical) and category. |
qartez_smells |
Code smell detector: finds god functions (high complexity + long body), long parameter lists, and feature envy (methods that use another type more than their own). Tuneable thresholds. |
qartez_health |
Prioritized fix list. Cross-references qartez_hotspots with qartez_smells and buckets files as Critical (hotspot + smell), High (hotspot only), or Medium (smell only). Each entry carries a concrete suggested refactor technique. |
qartez_refactor_plan |
Ordered, safety-annotated refactor plan for one file. Each step names a technique (Extract Method, Introduce Parameter Object), an estimated CC impact category (High/Medium/Low) with a range, and safety signals from impact, test coverage, and caller count. |
qartez_test_gaps |
Test coverage gap analysis via the import graph. Three modes: gaps ranks untested source files by risk, map shows test-to-source mappings, suggest recommends tests to run for a git diff range. |
qartez_knowledge |
Bus-factor analysis. Git-blame-based authorship at file and module level. Surfaces single-author files and modules where knowledge is concentrated in one contributor. |
qartez_blame |
Symbol-scoped git blame. Resolves a function/type name to its line range and blames only those lines: per-hunk commits/authors, or a per-author rollup with each author’s latest commit. |
qartez_semantic |
Semantic search using a local embedding model. Natural-language queries ranked by hybrid FTS5 + vector similarity (RRF). Requires the semantic cargo feature and a one-time model download (~270 MB). |
qartez_path |
Shortest call/reference path between two symbols. Forward BFS over the symbol-reference graph returns the ordered symbol/file chain plus a count of alternative shortest paths. Filter edges by kind (call or type). |
Refactor (unlock via qartez_tools)
| Tool | What it does |
|---|---|
qartez_rename |
Rename a symbol across the entire codebase. Definition, imports, all usages. Preview by default, apply=true to execute. |
qartez_move |
Move a symbol to another file and rewrite all import paths. One MCP call. |
qartez_rename_file |
Rename a file and update every import pointing to it. |
qartez_replace_symbol |
Replace a symbol’s whole line range with new source. Caller provides the full replacement including the signature; preview by default, apply=true executes atomically. |
qartez_insert_before_symbol |
Splice new code immediately before an anchor symbol. Anchor lookup goes through the indexed symbol table - no need for the exact surrounding context. |
qartez_insert_after_symbol |
Splice new code immediately after an anchor symbol. Same anchor-based addressing as qartez_insert_before_symbol. |
qartez_safe_delete |
Delete a symbol after reporting every file that still imports it. Refuses to apply when importers exist unless force=true. |
Meta (unlock via qartez_tools)
| Tool | What it does |
|---|---|
qartez_project |
Auto-detects your toolchain (Cargo, npm/bun/yarn, Go, Python, Make, Gradle) and runs test/build/lint/typecheck through a single tool. |
qartez_wiki |
Generates a markdown architecture wiki using Leiden community detection on the import graph. Partitions files into clusters, names each one, and emits ARCHITECTURE.md with inter-cluster edges. |
qartez_workspace |
Add or remove workspace domains at runtime. Registers external directories under a custom alias in .qartez/workspace.toml, indexes them, and purges them on removal. |
qartez_add_root |
Register an additional project root at runtime. Indexes the directory, refreshes pagerank/co-change, and hot-attaches a file watcher; the alias is optional (derived from the path basename) and persistence is toggleable for ephemeral roots. |
qartez_list_roots |
List every project root currently tracked by the server with its alias, source (cli/config/runtime), watcher attachment state, file count, and last index timestamp. |
qartez_maintenance |
Inspect and compact .qartez/index.db. Default action stats reports DB / WAL sizes, top tables, current workspace fingerprint, and last full-reindex timestamp. Other actions: checkpoint, optimize_fts (merge FTS5 segments), vacuum_incremental, vacuum, convert_incremental (one-shot conversion to auto_vacuum=INCREMENTAL), purge_stale (drop rows for roots no longer in the workspace). Use this on a bloated DB instead of deleting .qartez/index.db by hand. |
Tier management
| Tool | What it does |
|---|---|
qartez_tools |
Always visible. Lists all tiers and their tools. Use enable: ["analysis"], enable: ["all"], or disable: ["refactor"] to control which tools are exposed to the agent. Core tools cannot be disabled. |
Workflow prompts
Six ready-to-use recipes that chain the tools above in the right order. Invoke them as slash commands in Claude Code or any MCP client that supports prompts.
| Prompt | What it does |
|---|---|
/qartez_review |
Code review: blast radius, outline, references, co-change - then a focused checklist. |
/qartez_architecture [top_n] |
One-minute architecture overview grounded in PageRank data. |
/qartez_debug |
Definition + callers + callees + references in one shot. |
/qartez_onboard [area] |
Five-file reading list for new contributors, ranked by importance. |
/qartez_pre_merge |
Pre-merge safety check with a ship/hold recommendation. |
/qartez_arch_review [focus] |
Architecture risk audit: fragile hubs, tangled boundaries, security surface, complexity debt. |
Modification guard
Qartez ships a safety net that prevents your AI from blindly editing load-bearing files.
The qartez-guard binary hooks into Claude Code’s PreToolUse system and blocks Edit/Write/MultiEdit on any file that exceeds a PageRank or blast-radius threshold - until the AI calls qartez_impact first to acknowledge the risk.
How it works:
- AI tries to edit
src/server/mod.rs - Guard checks: PageRank 0.23 (> 0.05 threshold), blast radius 10 (>= 10 threshold)
- Edit is blocked with an explanation listing which thresholds fired
- AI calls
qartez_impact file_path=src/server/mod.rs- reviews the blast radius - Guard grants a 10-minute edit window for that file
- AI retries the edit - allowed
Zero configuration. Tuneable via QARTEZ_GUARD_PAGERANK_MIN, QARTEZ_GUARD_BLAST_MIN, QARTEZ_GUARD_ACK_TTL_SECS, or disabled with QARTEZ_GUARD_DISABLE=1.
Benchmarks
Not claims. Measured. Reproducible. Run make bench and verify yourself.
Headline
Aggregate token savings vs Glob + Grep + Read + git log: +91.8%
(sum of MCP 38,789 / sum of non-MCP 472,109 tokens across all 28 scenarios on the Qartez self-bench. Conservative under-count: 10 of 28 scenarios have an incomplete non-MCP sim - those rows still contribute their MCP tokens to both sums. On the 18 scenarios with a fair token-to-token comparison the saving rises to +94.5%.)
LLM-judge quality (claude-opus-4-6): MCP 8.3 / 10 vs non-MCP 4.3 / 10 across five axes (correctness, completeness, usability, groundedness, conciseness), n=28.
Session cost context. A typical Claude Code session starts at ~20,000 tokens of prompt overhead. A single make bench run saves ~433,000 tokens - ~21 empty sessions worth of budget bought back, just from routing questions through the right tool.
Per-tool breakdown (Rust self-bench)
18 tools with complete non-MCP simulations (fair token-to-token comparison):
| Tool | MCP tokens | Without MCP | Savings | Speedup |
|---|---|---|---|---|
qartez_cochange |
92 | 14,622 | +99.4% | 2x |
qartez_context |
107 | 4,489 | +97.6% | 533x |
qartez_find |
52 | 1,490 | +96.5% | 210x |
qartez_impact |
352 | 9,243 | +96.2% | 140x |
qartez_outline |
3,009 | 77,843 | +96.1% | 5x |
qartez_project |
68 | 1,394 | +95.1% | 0x |
qartez_unused |
468 | 6,750 | +93.1% | 22x |
qartez_deps |
166 | 2,286 | +92.7% | 118x |
qartez_map |
87 | 674 | +87.1% | 1x |
qartez_rename_file |
27 | 185 | +85.4% | 211x |
qartez_grep |
127 | 763 | +83.4% | 72x |
qartez_stats |
155 | 848 | +81.7% | 1x |
qartez_move |
161 | 701 | +77.0% | 159x |
qartez_calls |
564 | 2,409 | +76.6% | 3x |
qartez_refs |
201 | 692 | +71.0% | 26x |
qartez_read |
150 | 495 | +69.7% | 100x |
qartez_hierarchy |
735 | 2,056 | +64.3% | 127x |
qartez_rename |
439 | 648 | +32.3% | 11x |
10 additional analytical tools have no meaningful grep/read equivalent - they solve problems the non-MCP stack cannot solve at all:
qartez_hotspots, qartez_clones, qartez_smells, qartez_test_gaps, qartez_wiki, qartez_boundaries, qartez_trend, qartez_knowledge, qartez_diff_impact, qartez_security.
How it works under the hood
Four layers, computed once, queried from SQLite on every tool call.
1. Tree-sitter parsing
Every source file is parsed by a language-specific tree-sitter grammar. No LSP server, no per-language SDK installs, no cold-start penalty. The parser extracts symbols (functions, methods, types, constants), their signatures, line ranges, export visibility, import relationships, and - for 21 imperative languages - cyclomatic complexity per function.
2. Structural shape hashing
Function bodies are canonicalized into an AST skeleton (identifiers, literals, and comments normalized away) and hashed. Two symbols with the same hash are structural clones. That’s what qartez_clones queries.
3. Graph analysis
Import edges form a directed graph. Three algorithms run on top:
- PageRank - the same random-walk algorithm Google used for web pages. Applied to your import graph, it surfaces the files that form the architectural backbone of your project.
- Blast radius - reverse BFS that counts how many files are transitively affected by a change.
qartez_impactuses this to warn before edits. - Leiden clustering - community detection that partitions your codebase into logical modules for the auto-generated architecture wiki and the
qartez_boundariesstarter config.
4. Git history mining
Walks the last N commits (default 300) and counts file pairs that appear in the same commit. This reveals logical coupling that the import graph can’t see - files that aren’t linked by imports but are always edited together.
qartez_impact, qartez_context, and qartez_hotspots fuse these signals - PageRank + blast + co-change + complexity - into one ranked answer. No other MCP server combines all four.
Storage
Everything lives in .qartez/index.db - a single SQLite file with FTS5 full-text indices. On startup, Qartez re-parses only files whose modification time changed. The file watcher is enabled automatically while the server is running - edits and new files are re-indexed in the background with zero downtime. Pass --no-watch to disable it.
Transport
Qartez communicates over stdio (stdin/stdout JSON-RPC), the standard MCP transport. No HTTP server, no port allocation, no network exposure. The IDE launches the qartez binary as a child process and exchanges messages over pipes.
Supported languages
One binary. No per-language setup. All 37 languages parsed by tree-sitter (with regex fallbacks for formats lacking a compatible grammar). 21 imperative languages also get cyclomatic complexity per function, powering qartez_hotspots.
Highlights: TypeScript, Rust, Go, Python, Java, Kotlin, Swift, C#, C/C++, Ruby, PHP, Dart, Scala, Elixir, Zig, Lua, Haskell, OCaml, R, and 17 more. All 21 imperative languages include cyclomatic complexity scoring.
Comparison with alternatives
The MCP codebase-intelligence space is crowded in 2026. This section covers direct OSS competitors, enterprise platforms, and adjacent ecosystems. All star counts were cross-checked against each project’s GitHub repository in April 2026.
Direct OSS MCP competitors
Nine projects share the “MCP server for codebase intelligence” niche, sorted by GitHub stars.
| Project | Stars | Impl. | Indexing approach | Languages | MCP tools |
|---|---|---|---|---|---|
| Qartez (this repo) | new | Rust | tree-sitter + SQLite + PageRank + blast radius + co-change + complexity + clones + boundaries | 37 | 30 |
| Serena | 23k | Python | LSP (per-language language servers) | 46+ | ~35 |
| code-review-graph | 10.4k | Python | tree-sitter + SQLite + Leiden clustering | 23+ | 28 |
| Claude-Context | 5.9k | TypeScript | Embeddings + Milvus/Zilliz vector DB | 14 | 4 |
| CodeGraphContext | 3k | Python | tree-sitter + KuzuDB / FalkorDB / Neo4j | 14 | 21 |
| Codebase-Memory MCP | 1.6k | C | tree-sitter + SQLite + hybrid type resolution | 66 | 14 |
| Repowise | 1.2k | Python | Dependency graph + git history + LLM-generated docs | 14 | 7 |
| Code Index MCP | 903 | Python | tree-sitter (10 langs) + ripgrep fallback for 50+ | 10 + 50 | 11 |
| Codanna | 651 | Rust | tree-sitter + tantivy FTS + fastembed | 15 | ~9 |
Enterprise and IDE-native alternatives
Commercial platforms solving the same problem for users willing to trade local-first and open-source for polish or cross-repo scale:
- Sourcegraph Cody / Amp - compiler-grade SCIP indexers, official MCP server since 2026. Cloud-first, enterprise pricing.
- Augment Code - $227M Series B. Real-time semantic index + code-relationship graph across 400k+ files, official MCP server since Oct 2025. Cloud dependency.
- Deep Graph MCP (CodeGPT) - 392 stars. Cloud-hosted knowledge graph backend; swap
github.comtodeepgraph.coin any repo URL for a pre-built code graph. No local indexing needed. - JetBrains AI Assistant (IntelliJ 2025.2+) - embedded MCP server exposing IDE-grade symbols and diagnostics. JetBrains-only.
- Cursor - custom embedding model, team-shared index in Turbopuffer. Closed IDE, no MCP exposure.
- Windsurf Cascade - RAG-based M-Query retrieval. Closed IDE, no MCP server.
Qartez gives you the same structural intelligence these platforms sell - running entirely on your laptop, for free.
Adjacent ecosystems (different category, same problem)
- Aider repo-map - Paul Gauthier’s CLI pioneered tree-sitter + PageRank in October 2023. Lives inside the aider CLI, not as an MCP server. RepoMapper wraps the single
repo_mapoutput as MCP. - Continue.dev - MCP client, not server. Its documentation explicitly recommends pairing Continue with a dedicated code-graph MCP server - the role Qartez fills.
- Context7, Mem0, Pieces LTM - memory and documentation tools, not codebase indexers. Complementary, not competing.
- Block Goose, Cline, Codebuff - coding agent clients that consume MCP servers. They are the users of tools like Qartez.
What makes Qartez different
1. Quad-signal impact analysis. qartez_impact, qartez_diff_impact, qartez_context, and qartez_hotspots fuse PageRank importance, static blast radius, git co-change, and cyclomatic complexity into one ranked answer. No other project combines all four.
2. Hotspots, clones, boundaries, security, smells, test gaps, knowledge, and trends in one server. qartez_hotspots ranks the most dangerous functions in the repo by complexity x coupling x churn. qartez_clones finds duplicated logic via AST shape hashing. qartez_boundaries enforces architecture rules declared in .qartez/boundaries.toml. qartez_security scans for vulnerability patterns scored by PageRank. qartez_smells detects god functions, long parameter lists, and feature envy. qartez_test_gaps finds untested source files ranked by risk. qartez_knowledge surfaces bus-factor risks from git blame. qartez_trend tracks how a function’s complexity evolved commit by commit. These are eight separate commercial products elsewhere, one MCP call each here.
3. Refactoring through MCP with preview and apply. qartez_rename, qartez_move, and qartez_rename_file give the assistant atomic, reviewable refactors in a single MCP call. Serena offers rename via LSP (requires per-language server install); the remaining servers ship no refactoring tools at all.
4. Built-in safety net. The modification guard blocks your AI from editing high-impact files without reviewing the blast radius first. No other server in the main competitor table ships this.
5. Measured, not claimed. 28 scenarios, 8.3/10 vs 4.3/10 LLM-judge quality, per-tool token counts and latency. All reproducible with make bench (single-language) or make bench-all (5 languages with cross-language summary).
6. Rust-native, local-first, zero cloud dependency. Three binaries (qartez, qartez-guard, qartez-setup). No Python runtime, no vector database, no cloud account. Everything runs on your machine. No code leaves the box. An optional semantic cargo feature adds local embedding search, but the default build needs no model download.
Command-line options
Qartez also works as a standalone CLI. Run qartez (e.g., qartez map, qartez find Config, qartez impact src/server/mod.rs) to use any core or analysis tool directly from the terminal without an MCP client.
| Option | Description | Default |
|---|---|---|
--root |
Project root to index (repeatable for monorepos) | Auto-detected |
--reindex |
Force full re-index | Off |
--git-depth |
Commits to analyze for co-change | 300 |
--db-path |
Override index location | .qartez/index.db |
--no-watch |
Disable the automatic file watcher (on by default) | Watcher on |
--wiki |
Generate architecture wiki after indexing | Off |
--leiden-resolution |
Cluster granularity (larger = more clusters) | 1.0 |
--format |
Output format for CLI subcommands: human, json, compact |
human |
--log-level |
error, warn, info, debug, trace (any tracing directive accepted) |
info |
Contributing
Found a bug? Open an issue. Want to add a language, fix a parser, or improve a tool? Pull requests are welcome - read CONTRIBUTING.md and CODE_OF_CONDUCT.md first. Non-trivial PRs require signing the CLA.md.
git clone https://github.com/kuberstar/qartez-mcp.git
cd qartez-mcp
cargo build
cargo test
Release notes for every version live in CHANGELOG.md.
Security
Found a vulnerability? Do not open a public issue. Follow the disclosure policy in SECURITY.md.
License
Dual-licensed under the Qartez Small Team License (free for individuals and small teams) and the Qartez Commercial License (for everyone else). Read the full text in LICENSE, and see COMMERCIAL.md for the commercial terms summary. SPDX identifier: LicenseRef-Qartez-Dual.
Grep was for humans. Qartez is for agents. If Qartez saves you even 10% of your monthly AI bill, star the repo - it’s the only signal that tells other builders this approach is worth trying.
설치
This server does not publish a one-line install command.
Open the repository installation guide설정
{
"mcpServers": {
"qartez": {
"command": "/absolute/path/to/qartez",
"args": []
}
}
}