Gortex Code Intelligence
A local code graph that gives coding assistants precise context and cross-repository impact analysis.
SECURITY.md thoroughly describes operator versus agent channels, tracked-root path confinement, symlink resolution, Unix-socket permissions, network egress, persisted data, and external processes, and it explicitly warns that every agent session can read and write every tracked repository. Local-only defaults, opt-in hosted LLM and federation features, and mandatory authentication for non-loopback HTTP demonstrate meaningful least-privilege design. Deductions apply because any same-user process reaching the daemon socket receives authority over all repositories and the control surface, filesystem access is not session-isolated, loopback HTTP may be unauthenticated, and /v1 CORS defaults to *. Tracking and higher-risk features generally require an operator action, but ordinary agent file writes have no demonstrated per-operation confirmation. Source-derived prompts, notes, local persistence, and optional disclosure paths are explained well, while encryption at rest, secret detection, and credential redaction are not established. Dependencies and Actions are pinned, and release verification, signing, and SLSA controls are asserted; however, the supplied files show no dependency vulnerability scanning, SBOM, or vulnerability-remediation evidence, and the dependency surface is extensive. Non-mutating edit previews are documented, but a general backup, transaction, or undo facility for completed writes is not. The full Apache-2.0 license, copyright holder, and contact address provide strong attribution; registry non-verification is treated only as unknown identity.
README, SECURITY.md, go.mod, and CI present a broadly coherent account of the local architecture, platforms, CGO, SQLite, static distribution, and optional components. CI covers Linux, macOS, Windows, static linkage, and several embedding builds. Deductions apply because the README's opt-in telemetry description sits uneasily beside SECURITY.md's categorical “No telemetry,” and “zero dependencies” describes distribution convenience rather than the substantial build dependency graph. go.mod pins a very large direct and indirect dependency set, while CI pins Actions to commits and exercises several build forms. Availability is not fully established because Go 1.26.6 and some future-dated or very recent module revisions are only declared in the supplied evidence, not independently confirmed. Property tests demonstrate graceful preservation of original output on augmentation timeout, connection failure, or empty results, and readable bridge error formatting, but there is no comprehensive product-level error catalog, diagnostic contract, or recovery guide.
The material clearly targets AI coding agents, IDEs, CLI, MCP, HTTP, and a web UI, with concrete scenarios covering cross-repository analysis, editing, review, search, contract matching, and large repositories. It names 19 agent integrations and supports the three major desktop operating-system families. SECURITY.md precisely states read/write boundaries, lack of session isolation, networking, subprocess execution, and remote-deployment limitations, earning full capability-boundary credit. Triggering evidence includes minimum-pattern gating for grep augmentation, fallback behavior, and opt-in network or process features, but it does not cover routing and invocation precision across the claimed 175 MCP tools. Environment fit is strongly supported by the cross-platform single binary, static Linux checks, Windows-specific path tests, Linux/macOS race tests, and multiple installation channels.
The README has strong organization around installation, quick start, architecture, scale, features, and a topic-based documentation index. Installation guidance includes claimed SHA256 and cosign verification, alternative package formats, and source-build requirements. CLI, MCP, /v1 HTTP, and gortex-* bridge names appear internally consistent, but the supplied evidence contains no compatibility history or deprecation examples, so long-term naming stability is not fully demonstrated. Quick-start commands, tables, examples, and tool-chaining hints are extensive, although no actual centralized FAQ content is supplied. SECURITY.md gives unusually concrete limitations concerning shared authority, loopback exposure, prompt injection, subprocesses, and data egress. The complete Apache-2.0 text and copyright notice justify full license credit. A versioning document and release page are referenced, but neither policy contents nor a changelog is included. A named maintainer, email, private vulnerability channel, and Discord establish an update path, while team governance, support horizons, and succession are absent; publisher registry status remains unknown.
Bridge property tests require user-facing output to be readable plain text, label errors, and include next-step tool hints. The README additionally describes CLI, JSON, MCP, API, graph UI, and GCX1 consumption formats, providing strong output-usability evidence. A persistent code graph, cross-repository call and contract links, impact analysis, live overlays, and speculative edits offer clear marginal value over ordinary file reads. Scale tables, throughput and memory figures, a benchmark workflow, a reproducible-benchmark pointer, and token-savings examples support the cost-benefit case. Deductions apply because the 50x and 27% savings remain largely first-party claims within the supplied files, the largest listed index uses about 5.07 GB peak heap, and the 175-tool surface plus extensive dependency graph impose setup and maintenance costs.
Many claims point to repository documentation on installation, languages, architecture, benchmarks, telemetry, and versioning. CI directly exposes build, test, static-link, and benchmark commands, while go.mod makes dependency versions traceable. The linked documents themselves are mostly absent from the supplied material, however, so claims such as 257 languages, 19 agents, 175 tools, SLSA level 3, the VirusTotal result, and token reductions cannot be checked item by item here. README, SECURITY.md, CI, tests, and the dependency manifest provide useful cross-corroboration for platform support, architecture, safety boundaries, and graceful output fallback; performance and savings evidence remains predominantly first-party. The security policy carefully distinguishes defaults, explicit grants, and missing protections, but marketing maxima and phrases such as “zero dependencies” and “No telemetry” do not always cleanly separate distribution dependencies, build dependencies, and optional configuration.
- Every agent session shares filesystem read/write authority over all tracked repositories; workspace and project scopes constrain graph queries, not filesystem access.
- When HTTP is enabled, use an authentication token even on loopback, narrow the default CORS wildcard, and grant browser origins carefully.
- Hosted or subprocess LLM providers, federation, PR tooling, and opt-in pprof can move source-derived or sensitive process data beyond the default local boundary.
- Agent writes are first-class, but per-write confirmation and general rollback are not demonstrated; review changes like pull requests and retain external version-control recovery.
- Headline claims including 257 languages, 50x token reduction, SLSA level 3, and malware-scan results are not fully reproducible from the supplied files alone.
- The dependency graph is extensive. Versions and Actions are pinned, but the evidence does not show an SBOM, vulnerability scan, or dependency-remediation process.
What does this agent do, and when should you use it?
Gortex is a local code-intelligence engine that parses 257 languages or grammars and stores functions, classes, call chains, HTTP routes, and cross-service contracts in a persistent knowledge graph. It exposes that graph through a CLI, MCP Server, versioned HTTP `/v1/*` API, and web UI, with multi-repository operation enabled by default. A long-running daemon combines a shared SQLite graph store, filesystem watching, incremental indexing, and per-session isolation for multiple editor clients. Its operations include symbol lookup, call-chain and blast-radius analysis, dataflow, clone detection, refactoring support, code actions, PR risk analysis, and change verification. It ships as a single static binary for macOS, Linux, and Windows; core operation needs neither an external model nor a model download, while nine optional LLM provider paths are documented.
After installation, gortex track adds one or more local repositories to the workspace. MultiIndexer analyzes their source with tree-sitter ASTs, in-process resolvers, and compiler-grade resolution for selected languages, then writes nodes and edges to the shared SQLite graph store. MultiWatcher processes filesystem changes, while CrossRepoResolver creates type-aware, evidence-gated relationships between repositories. Coding assistants query symbols, references, call chains, contracts, and change impact through MCP tools, the CLI, or HTTP /v1/*; preview_edit and simulate_chain evaluate a WorkspaceEdit without touching disk. gortex prs analyzes open pull requests for impact and merge-order conflicts, while gortex review produces line-anchored findings with a BLOCK, REVIEW, or APPROVE verdict. The web UI visualizes graphs and contracts, and gortex savings records token savings relative to naive file reads.
- A team maintaining several service repositories can trace cross-repository call chains and determine which HTTP, gRPC, GraphQL, messaging, or environment-variable consumers are affected by a contract change.
- Developers using Claude Code, Codex CLI, Cursor, Windsurf, or VS Code/Copilot can give their assistants targeted symbol and graph context instead of repeatedly loading entire source files.
- An engineer preparing a shared API or type refactor can run blast-radius queries and use
preview_editorsimulate_chainbefore writing the proposed WorkspaceEdit to disk. - A team triaging pull requests can use
gortex prsfor per-PR impact, shared-community merge conflicts, ranking, and reviewer suggestions, followed bygortex reviewfor line-level findings. - An organization that cannot upload private source code can keep indexing, storage, and standard queries on its own machine with telemetry disabled by default.
- Maintainers of large, polyglot repositories can use the built-in hybrid BM25, vector, and RRF search without first downloading an embedding model.
What are this agent's strengths and limitations?
- Multi-repository analysis is native, including matching for HTTP, gRPC, GraphQL, messaging, WebSocket, environment-variable, OpenAPI, and Temporal contracts.
- One static binary provides a CLI, MCP server, HTTP API, daemon, and web UI, while core indexing and queries require no external model service.
- It recognizes 257 languages or grammars and adds stronger resolution for languages including Python, TypeScript/JavaScript, Go, Java, and Rust.
- The feature set extends beyond search to speculative edits, live unsaved-buffer overlays, impact analysis, PR review, and composable safety checks.
- Nineteen coding assistants are supported out of the box, with setup commands that configure detected clients.
- Releases advertise SHA256 and cosign/Sigstore verification plus SLSA Level 3, and telemetry is disabled by default.
- Indexing very large repositories can require substantial resources: the published Linux-kernel measurement is about three minutes with 5.07 GB peak heap.
- Language handling uses several tiers—bespoke tree-sitter extraction, regex, and forest-backed signatures—so support for 257 grammars does not imply identical analysis depth for every language.
- Source builds require Go 1.26+ and CGO because of tree-sitter C bindings, adding local toolchain requirements.
- Optional MiniLM, Ollama, OpenAI, and other LLM integrations introduce extra runtimes, services, or credentials; complete setup details are absent from the supplied material.
- The MCP surface is broad: the material cites 175 configurable tools as well as a general “100+” count, so adopters must decide which tools to expose.
- The up-to-50× token reduction and performance figures come from the project's reproducible benchmarks; actual savings will depend on repository structure and assistant behavior.
How do you install or deploy this agent?
On macOS or Linux:
curl -fsSL https://get.gortex.dev | shOn Windows PowerShell:
irm https://get.gortex.dev/install.ps1 | iexThe installer detects the operating system and architecture, verifies SHA256 and cosign data, and installs the binary on PATH. Core local use requires no API credentials, external model, or model download. Homebrew, .deb, .rpm, .apk, Scoop, signed binaries, and source builds are also listed; building from source requires Go 1.26+ and CGO for the tree-sitter C bindings.
How do you use this agent?
Perform the one-time machine setup and start the background daemon:
gortex install
gortex daemon start --detachTrack a repository and initialize its assistant configuration:
gortex track ~/projects/myapp
cd ~/projects/myapp && gortex initgortex install configures MCP, skills, and slash commands. The repository-level gortex init creates .mcp.json, hooks, and community routing so detected supported coding assistants can query the graph. No credentials are required for this core workflow. The supplied material names optional OpenAI, Anthropic, Ollama, Bedrock, and other LLM paths but does not provide their credential configuration.
FAQ
Does Gortex send source code or telemetry to an external service?
Is MCP mandatory?
/v1/* API, and web UI. MCP is a primary coding-assistant integration, but it is not the only access path.Can it analyze multiple repositories and service contracts together?
What credentials are needed for the first working setup?
Can it evaluate a change before modifying files?
preview_edit and simulate_chain model WorkspaceEdit effects without touching disk. verify_change and check_guards add checks for broken callers and guard violations.