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 19 coding agents. Up to 50× fewer tokens per response. Reproducible benchmarks.

19 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, Kimi) 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 (20) — gortex init configures 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), store-native FTS5/BM25 + vector with adaptive alpha fusion, zero deps; opt-in MiniLM / Ollama / OpenAI → docs/semantic-search.md
• Speculative execution — preview_edit / simulate_chain answer "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, an on-disk SQLite graph store, incremental 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_config flag broken callers, guard violations, stale docs before they ship
• PR review, end to end — gortex prs triages open PRs (per-PR blast radius, merge-order conflicts via shared communities, AI-ranked queue, reviewer suggestions); gortex review emits 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; honours DO_NOT_TRACK → docs/telemetry.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    ███████████████░   93.3%  saved 11,246,094 / 12,050,716 tokens  $168.69

--verbose adds the per-tool breakdown; --json is machine-readable. Full reference: docs/savings.md.

Architecture

gortex binary
  CLI (cobra)    ──> MultiIndexer ──> Graph store (SQLite, shared, per-repo indexed)
  MCP (stdio)    ──────────────────> Query Engine (repo/project/ref scoping)
  HTTP /v1/*     ──────────────────> same tools + /v1/graph + /v1/events (SSE)
  Daemon (unix)  ──────────────────> shared graph for every MCP client, session isolation
                  MultiWatcher    <── filesystem events (fsnotify, per-repo)
                  CrossRepoResolver ──> cross-repo edge creation (type-aware)
                  Persistence     ──> the same SQLite store, written as it indexes

Data flow, graph schema (node and edge kinds, multi-repo fields, test taxonomy), persistence model: docs/architecture.md.

Documentation

| Topic | Reference | | --- | --- | | First-time walkthrough | onboarding.md | | Installation & supply-chain verification | installation.md | | Full feature catalog | features.md | | CLI reference | cli.md | | MCP tools, resources, prompts | mcp.md | | Multi-repo workspaces | multi-repo.md | | HTTP server + Web UI + MCP 2026 transport | server.md | | Cross-repo API contracts | contracts.md | | Semantic search | semantic-search.md | | Optional LLM features | llm.md | | LSP integration | lsp.md | | Per-community skills & agent usage | skills.md | | AI agent adapters (20) | agents.md | | Supported languages (257) | languages.md | | Token savings | savings.md | | GCX1 wire format | wire-format.md | | Architecture & graph schema | architecture.md | | Evaluation methodology | 04-evaluation/ | | Telemetry & privacy | telemetry.md | | Versioning policy | versioning.md |

Building from source

make build          # binary with version stamping
make test           # go test -race ./...
make lint           # golangci-lint

Requires Go 1.26+ and CGO (for tree-sitter C bindings).

License

Apache License 2.0. See LICENSE.md. Copyright 2024-2026 Andrey Kumanyaev .

Contributing

See CONTRIBUTING.md for guidelines on adding features, language extractors, and submitting PRs.

New contributors are very welcome — join us on Discord and introduce yourself. It's the easiest place to ask questions, check whether someone is already working on something, and get feedback on a design before you write the code.