gortex
by zzet
High-performance code-intelligence engine for AI agents and IDE, supports 257 languages, multi repositories, based on graph, with access via CLI, MCP Server, and API. AI coding agents teammate - expose only needed information, cutting token usage up to 50x. 100% local. Discord: https://discord.gg/ysC2prTGD
870stars
74forks
Go
Added 6/10/2026
AI Agentsai-toolsantigravityclaude-codecode-analysiscode-assistantcontext-windowcontext-window-optimizationcontext-window-optimizercopilotcursordeveloper-toolsgraphragkiroknowledge-graphlocal-firstmcp-serverpromptsskillstokenswindsurf
Installation
# Add to your Claude Code skills
git clone https://github.com/zzet/gortexGetting Started
Guides for using ai agents skills like gortex.
- Caveman: Cut Claude Token Use by 65%How agent-side prompt compression works, when to use it, and when not to.
- What is an AI Skills Marketplace?Definitions, how marketplaces work, and how to choose between them in 2026.
- Getting Started with AI SkillsFirst-time install walkthrough for Claude Code, Codex CLI, and ChatGPT.
Security ReportVerified
Last scanned: 6/10/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-06-10T08:08:37.064Z",
"npmAuditRan": true,
"pipAuditRan": true
}High-performance and efficient code-intelligence engine for AI agents and IDE
Indexes code into graph and exposes it via CLI, MCP Server, and web UI. Multi-repository support by default.
Single static binary for macOS, Linux, and Windows — no dependency chain, simple installation and use.
High-quality parsing 257 languages/grammars through tree-sitter AST analysis, in-process resolvers, enhanced with compiler-grade resolution for Python, TypeScript / JavaScript, PHP, C#, Go, C, C++, Java, Kotlin, Swift, Zig, Rust, Ruby, Elixir, Ocaml, Haskell, and others - producing a persistent provenance-tiered knowledge graph of functions, classes, call chains, HTTP routes, and cross-service contracts and calls with a strong confidence model. 175 (configurable) MCP tools - use only what you need. Zero dependencies. Plug and play across 18 coding agents. Up to 50× fewer tokens per response. Reproducible benchmarks.
18 AI coding agents (Claude Code, Kiro, Cursor, Windsurf, VS Code / Copilot, Continue.dev, Cline, OpenCode, Antigravity, Codex CLI, Gemini CLI, Zed, Aider, Kilo Code, OpenClaw, Hermes, Oh My Pi, Pi) supported out of the box.
One install configures every one detected on your machine — see docs/agents.md.
Why it matters
- 50× fewer tokens per response — graph-native lookups beat naive file reads. Agents read just what they need, not the full file, not the 500-line file around it.
- Full development cycle - no 'read file before edit'. Agents ask for sources, tell what to change, and don't waste context of reading noise.
- 257 languages/grammars - every file in the repository reachable; no mix of tools and bloating/hallycinating agents. Three tiers (bespoke tree-sitter, regex, forest-backed signatures) plus Jupyter and Databricks notebooks → docs/languages.md
- Cross-repo by default — N repos in one graph; contracts, references, and call chains span repo boundaries with evidence-gated resolution, contract matching, impact analysis, per-session isolation → docs/multi-repo.md
- Extreamly fast analysis — a precomputed depth-3 reach index turns blast-radius queries into O(seeds × reach) map lookups. Safe to ask "what breaks if I change this?" on every edit. No dozens of tool calls to grasp context.
- Zero external dependencies — single binary, everything in-process. No network, no model download to get started. Install, start daemon, use.
- Agent integrations (17) —
gortex initconfigures every detected coding assistant on the machine → docs/agents.md - 100+ MCP tools, 16 resources, 3 prompts — symbol lookup, call chains, blast radius, dataflow, clone detection, refactoring, code actions → docs/mcp.md
- Semantic search default-on — baked GloVe-50d (3.8 MB embedded), hybrid BM25 + vector + RRF, zero deps; opt-in MiniLM / Ollama / OpenAI → docs/semantic-search.md
- Speculative execution —
preview_edit/simulate_chainanswer "what would change if I applied this WorkspaceEdit?" without touching disk - Live editor overlays — push unsaved buffers as a shadow graph; tools read through it. Branching for parallel speculative sessions
- GCX1 wire format — published, round-trippable. An additional −27% tokens vs JSON at same fidelity → docs/wire-format.md
- Long-living daemon — one process serves every IDE window; live fsnotify, on-disk snapshots, restart, OS-supervised lifecycle
- 9 LLM providers (optional) — local llama.cpp, Anthropic, OpenAI, Ollama, Claude / Codex CLI subprocess, Gemini, Bedrock, DeepSeek → docs/llm.md
- Composable safety —
verify_change,check_guards,audit_agent_configflag broken callers, guard violations, stale docs before they ship - PR review, end to end —
gortex prstriages open PRs (per-PR blast radius, merge-order conflicts via shared communities, AI-ranked queue, reviewer suggestions);gortex reviewemits line-anchored findings with a BLOCK/REVIEW/APPROVE verdict from a graph-grounded rulepack; MCP tools (pr_risk,get_pr_impact,review,review_pack,post_review, …) expose it to agents → docs/cli.md - HTTP server + Web UI — versioned
/v1/*API + MCP 2026 Streamable HTTP; standalone Next.js 15 UI with five 3D graph modes → docs/server.md - Telemetry off by default — opt-in anonymous tool/command counts only (no code, paths, names, or exact counts); nothing transmitted unless you configure an endpoint.
gortex telemetry on|off|status; honoursDO_NOT_TRACK→ docs/telemetry.md
Full catalog of features: docs/features.md. Complete CLI reference: docs/cli.md.
Install
# macOS / Linux
curl -fsSL https://get.gortex.dev | sh
# Windows (PowerShell)
irm https://get.gortex.dev/install.ps1 | iex
Detects OS/arch, verifies SHA256 + cosign, installs to PATH. Re-run to upgrade. Homebrew, .deb / .rpm / .apk, scoop, signed binaries, and from-source builds: docs/installation.md.
Quick Start
gortex install # one-time machine setup (MCP, skills, slash commands)
gortex daemon start --detach # background daemon
gortex track ~/projects/myapp # add a repo
cd ~/projects/myapp && gortex init # per-repo: .mcp.json, hooks, community routing
Your AI assistant now uses graph queries. Full 15-minute walkthrough: docs/onboarding.md.
Cross-Repo API Contracts
Gortex auto-detects API contracts across repos and matches providers to consumers, surfaced via the contracts MCP tool and the web UI Contracts page.
| Contract type | Detection | Provider | Consumer |
|---|---|---|---|
| HTTP routes | Framework annotations (gin, Express, FastAPI, Spring, …) | Route handler | HTTP client calls (fetch, http.Get) |
| gRPC | Proto service definitions | Service RPC | Client stub calls |
| GraphQL | Schema type/field definitions | Schema | Query/mutation strings |
| Message topics | Kafka / RabbitMQ / NATS / Redis pub/sub | Publish calls | Subscribe calls |
| WebSocket | Event emit/listen patterns | emit() |
on() |
| Env vars | os.Getenv, process.env, .env files |
Setenv / .env |
Getenv / process.env |
| OpenAPI | Swagger / OpenAPI spec files | Spec paths | (linked to HTTP routes) |
| Temporal workflows | Go / Java SDK annotations | Activity / workflow function | ExecuteActivity / ExecuteChildWorkflow |
Contracts are normalised to canonical IDs (e.g. http::GET::/api/users/{id}) and matched across repos to detect orphan providers / consumers and mismatches. See docs/contracts.md.
Scale — battle-tested on large repos
Measured on an Apple Silicon laptop with the default CGO build.
| Repository | Files | Nodes | Edges | Index time | Throughput | Peak heap |
|---|---|---|---|---|---|---|
| torvalds/linux | 70,333 | 1,690,174 | 6,239,570 | ~3 min | 300 files/s | 5.07 GB |
| microsoft/vscode | 10,762 | 204,501 | 808,902 | ~1 min | 143 files/s | 580 MB |
| zzet/gortex (self) | 430 | 5,583 | 53,830 | 3.4s | 127 files/s | 52 MB |
Parsing dominates wall time (65–80 %); reference resolution and search-index build scale sub-linearly.
Token savings dashboard
gortex savings reports tokens saved vs naive file reads — per-call, per-session, and cumulative across restarts, priced in USD against the headline model.
Gortex Token Savings
====================
Cost avoided: $168.69 (claude-opus-4) across 1,878 calls · 11,246,094 tokens saved
Today ████████░░░░░░░░ 50.0% saved 9,200 / 18,400 tokens $0.14
Last 7 days ██████████░░░░░░ 62.5% saved 60,100 / 96,200 tokens $0.90
All time ███████████████░
Frequently Asked Questions
What is gortex?
gortex is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by zzet. High-performance code-intelligence engine for AI agents and IDE, supports 257 languages, multi repositories, based on graph, with access via CLI, MCP Server, and API. AI coding agents teammate - expose only needed information, cutting token usage up to 50x. 100% local. Discord: https://discord.gg/ysC2prTGD. It has 870 GitHub stars.
Is gortex safe to use?
Yes. gortex passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
How do I install gortex?
Clone the repository with "git clone https://github.com/zzet/gortex" and add it to your Claude Code skills directory (see the Installation section above).
What programming language is gortex written in?
gortex is primarily written in Go. It is open-source under zzet on GitHub, so you can review or fork the full source.
Are there alternatives to gortex?
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh gortex against similar tools.
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