# repo-graph

[![repo-graph MCP server](https://glama.ai/mcp/servers/James-Chahwan/repo-graph/badges/card.svg)](https://glama.ai/mcp/servers/James-Chahwan/repo-graph)

**Structural graph memory for AI coding assistants.** Map your codebase. Navigate by structure. Read only what matters.

repo-graph gives LLMs a map of your codebase — entities, relationships, and flows — so they can navigate to the right files without reading everything first.

Instead of flooding an LLM's context window with your entire codebase (or hoping it guesses right), repo-graph builds a lightweight graph of what exists, how things connect, and where the entry points are. The LLM queries the graph, finds the minimal set of files it needs, and reads only those.

It pays off most where that's hardest to do by hand: **large repos, monorepos that span several languages, and multi-service systems** where a feature's path crosses files, stacks, and service boundaries. On a small single-language project a model can just read the files — see [Where it fits best](#where-it-fits-best) for the honest sweet spot.

**Install in one click:**

[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://vscode.dev/redirect/mcp/install?name=repo-graph&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22mcp-repo-graph%22%2C%22--repo%22%2C%22.%22%5D%7D)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=repo-graph&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22mcp-repo-graph%22%2C%22--repo%22%2C%22.%22%5D%7D&quality=insiders)
[![Add to Cursor](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/install-mcp?name=repo-graph&config=eyJjb21tYW5kIjoidXZ4IiwiYXJncyI6WyJtY3AtcmVwby1ncmFwaCIsIi0tcmVwbyIsIi4iXX0%3D)

Or one command in your terminal wires up every agent you have: `uvx mcp-repo-graph install` (see [Install](#install)).

---

> ### ⚠️ Upgrading to 0.5.0
>
> **The engine package was renamed `repo-graph-py` to `glia-py`.** If you install with `uvx` or
> `pip install mcp-repo-graph`, you don't have to do anything. The new engine is pulled in for you.
>
> You only need to act if you **import the engine directly**:
>
> ```diff
> - import repo_graph_py as rg
> + import glia_py as rg
> ```
>
> Three other things changed in that same release:
>
> - **The answers are Python objects, not JSON strings.** `find`, `resolve`, `blast_radius`,
>   `cross_stack_trace` and `governing_docs` return a `{"results": [...], "absence": {...}}` dict.
>   If you were doing `json.loads(...)` on a result, drop it.
> - **`find_node` and `find_nodes_by_qname` are gone.** One `find(query, top_k)` replaces both.
> - **The graph cache moved** from `.ai/repo-graph/` to `.glia/graph/`. It's rebuilt automatically,
>   so you can delete the old directory. The new one ignores itself and never shows up in
>   `git status`.
>
> The six MCP tools are unchanged (`orient`, `find`, `impact`, `trace`, `read`, `refresh`), so
> nothing in your agent config needs touching. Full detail in the
> [0.5.0 release notes](https://github.com/James-Chahwan/repo-graph/releases/tag/v0.5.0).

## Demo

https://github.com/user-attachments/assets/a1e4171b-b225-40d4-9210-39453e14b76a

https://github.com/user-attachments/assets/fc3191e5-fc35-4bd7-8372-72af55995883

Same bug, same model, same prompt — the only difference is whether repo-graph is installed.

**The task:** fix a reversed comparison operator in a Go + Angular monorepo.

*(Recorded on an earlier engine, which mapped that repo to 566 nodes / 620 edges. The 0.5.0 engine extracts far more from the same code, 2,939 nodes and 5,129 edges, so the graph the model gets today is richer than the one in the video. The token and time figures are from the recorded run and are left as measured.)*

| | Without repo-graph | With repo-graph |
|---|---|---|
| **Tokens used** | 75,308 | 29,838 |
| **Time to fix** | 4m 36s | ~30s |
| **Files explored** | ~15 (grep, read, grep, read...) | 2 (trace lookup + handler file) |
| **Outcome** | Found and fixed the bug | Found and fixed the bug |

**2.5x fewer tokens. ~9x faster. Same correct fix.**

### How the test was run

Both runs used identical conditions to keep the comparison fair:

- **Same model**: Claude Opus, 100% (no Haiku routing)
- **Same prompt**: *"Groups that were created recently are showing as closed, and old groups show as open. This is backwards — new groups should be open for members to join. Find and fix the bug."*
- **Fresh context**: each run started from `/clear` with no prior conversation
- **No other tools**: CLAUDE.md, plugins, hooks, and all other MCP servers were removed for both runs — the only variable was whether repo-graph was installed
- **No hints**: the prompt describes the symptom, not the location — Claude has to find `group_controller.go:57` on its own

Without repo-graph, Claude greps for keywords, reads files, greps again, reads more files, and eventually narrows down to the bug. With repo-graph, Claude calls `trace("groups")`, gets back the exact handler function and file, reads it, and fixes it.

> Browse [pre-generated examples](examples/) for [FastAPI](examples/fastapi/), [Gin](examples/gin/), [Hono](examples/hono/), and [NestJS](examples/nestjs/) — real graph output you can inspect without installing anything.

## The problem

LLMs working on code waste most of their context on orientation:

- Reading files that turn out to be irrelevant
- Missing connections between components in different languages
- Not knowing where a feature starts or what it touches
- Loading 50 files when 5 would do

This is expensive, slow, and gets worse as codebases grow.

## How repo-graph solves it

repo-graph scans your codebase once and builds a graph of:

- **Entities**: modules, packages, classes, functions, routes, services, components
- **Relationships**: imports, calls, handles, defines, contains, cross-stack HTTP
- **Flows**: end-to-end paths from entry point to data layer

Then it exposes 6 MCP tools that let the LLM:

1. **Orient** — "What languages are in this repo? What are the main features? Where is the graph blind?"
2. **Navigate** — "Trace the login flow from route to database" / "What's the shortest path between UserService and the payments API?"
3. **Scope** — "Which nodes matter for this bug?" / "Give me just the files I need for this fix"
4. **Assess** — "What's the blast radius of changing this function?" / "What here is dead code?"

The LLM gets structural context in a few hundred tokens instead of reading thousands of lines.

## Where it fits best

repo-graph earns its keep when a codebase is bigger or more tangled than the model can hold in its head at once. The payoff scales with three things:

- **Size** — enough files that reading the relevant ones blows the context budget.
- **Complexity** — rules, indirection, and layers, so "just read it" stops working.
- **Cross-boundary reach** — the answer spans files, languages, or services that a text search can't link.

Strong fits:

- **Monorepos** — a frontend calling a backend across a language boundary. repo-graph links the HTTP call to the route it hits and the handler behind it, which a text search can't do because the two sides share no string. Point `--repo` at the monorepo root and a single graph spans every project. *(The demo above is exactly this: Go + Angular in one repo.)*

  Other tools link `fetch`/`axios` to Express, Fastify and Koa routes. What differs here is reach: the same pairing runs across Go, Python, Java, C#, Rust, PHP, Ruby and the rest, in one graph, and covers gRPC, GraphQL, WebSockets, queues and events on the same footing. That breadth is not benchmarked against them, so take it as a design difference rather than a measured win.
- **Multi-service / polyrepo systems** — drop the services under one directory and point `--repo` at it; the graph traces a feature across service boundaries in one call.
- **Large single codebases** — thousands of files where orientation itself is the cost.
- **Unfamiliar or legacy code** — where you don't yet know what touches what.

Where it *doesn't* pull its weight: a **small, single-language repo with a clear task**. The model can just read the files — grep wins and the graph is overhead. Don't reach for it to shave tokens, either: the MCP layer is a fixed per-turn cost, so on easy tasks it can cost *more*. The token win shows up only when it heads off a grep-read-grep spiral (like the demo above). What it reliably buys you is **correct, complete, cross-boundary answers in a few calls** on code too big or too interconnected to fit in context — yours or the model's. (Don't want the MCP layer at all? [Skip it](#use-it-without-mcp) and call the engine directly.)

## Use it without MCP

The MCP server is the zero-config path, but the graph isn't tied to it. The engine ships as a plain Python wheel — `pip install glia-py` — so you can build the graph and call the same answer primitives directly, from a script or your own tooling, with **none of the per-turn MCP cost**:

```python
import glia_py as rg

g = rg.load_from_gmap(rg.default_gmap_dir("."), ".")   # builds it if there's no cache yet

g.find("checkout")                              # ranked, located nodes for a name
g.blast_radius(["checkout", "Cart.add"], "both")  # many seeds, one walk, one ranking
g.cross_stack_trace("notifications")            # feature path across the stack, mechanism-labelled
g.resolve(open("error.log").read())             # stacktrace / test / diff → the nodes that matter
g.coverage()                                    # where extraction is partial (grep those)
```

Each of these returns plain Python — a `{"results": [...], "absence": {...}}` dict for the lookups,
a list for `coverage()`. When `results` is empty, `absence` says *why*, so a script can branch on it
instead of guessing.

Same graph, same answers — just without the tool schemas in your context. It's the same Rust engine ([glia](https://github.com/James-Chahwan/glia)) the MCP server wraps; `glia-py` is its published wheel. Good for CI checks, batch analysis, or wiring the graph into your own agent.

## Supported languages

| Language | Detection | What it extracts |
|----------|-----------|-----------------|
| **Go** | `go.mod` | Packages, functions, HTTP routes (gin/echo/chi/stdlib), imports |
| **Rust** | `Cargo.toml` | Crates, modules, structs, traits, functions, routes (Actix/Rocket/Axum) |
| **TypeScript** | `tsconfig.json` / `package.json` | Modules, classes, functions, import relationships |
| **React** | `react` in `package.json` | Components, hooks, context providers, React Router routes, fetch/axios calls, flows |
| **Angular** | `@angular/core` in `package.json` | Components, services, guards, DI injection, HTTP calls, feature flows |
| **Vue** | `vue` in `package.json` | SFCs, composables, Vue Router routes, fetch/axios calls |
| **Python** | `pyproject.toml` / `setup.py` / `requirements.txt` | Packages, modules, classes, functions, routes (Flask/FastAPI/Django) |
| **Java/Kotlin** | `pom.xml` / `build.gradle` | Packages, classes, routes (Spring/JAX-RS/Ktor/WebFlux/Micronaut) |
| **Scala** | `build.sbt` | Packages, objects/classes/traits, routes (Play/Akka HTTP/http4s) |
| **Clojure** | `project.clj` / `deps.edn` | Namespaces, defn/defprotocol/defrecord, routes (Compojure/Reitit) |
| **C#/.NET** | `.csproj` / `.sln` | Namespaces, classes, routes (ASP.NET/Minimal API) |
| **Ruby** | `Gemfile` / `.gemspec` | Files, classes, modules, Rails routes |
| **PHP** | `composer.json` | Namespaces, classes, interfaces, routes (Laravel/Symfony) |
| **Swift** | `Package.swift` / `.xcodeproj` | Files, types (class/struct/enum/protocol/actor), Vapor routes |
| **C/C++** | `CMakeLists.txt` / `Makefile` / `meson.build` | Sources, headers, classes, structs, enums, namespaces, includes |
| **Dart/Flutter** | `pubspec.yaml` | Modules, classes, widgets, go_router/shelf routes |
| **Elixir/Phoenix** | `mix.exs` | Modules, functions, Phoenix router scopes + routes |
| **Solidity** | `.sol` files / `foundry.toml` / `hardhat.config.*` | Contracts, interfaces, libraries, events, inheritance |
| **Terraform** | `.tf` files | Modules, resources, variables, outputs, module sources |
| **SCSS** | `.scss` files present | File-level bloat analysis |

Cross-cutting extractors (work across all languages):

- **Cross-stack HTTP**: frontend `fetch`/`axios` calls linked to the backend route they hit, and the handler behind it
- **WebSockets**: handlers and clients (gorilla, browser, Python, Java, C#), paired by path
- **gRPC**: services, methods and message types from `.proto`, plus client stubs and server implementations
- **GraphQL**: resolvers and the operations that call them
- **Queues**: consumers and producers (Celery, Dramatiq, BullMQ, Sidekiq, Oban, NATS), with const-resolved topics
- **Events**: emitters and handlers
- **Cron jobs**: scheduled entry points
- **Page navigation**: frontend routes and the links between them (`NAVIGATES_TO`)
- **Data sources**: DB / cache / queue / blob / search / email clients, and which code touches which
- **Data entities**: shared schemas and the code that reads or writes them
- **CLI entrypoints**: Python click, JS commander/yargs, Go cobra, Rust clap, Java picocli, C# System.CommandLine and Spectre
- **Contracts**: OpenAPI / AsyncAPI / Pact operations linked to the routes that implement them
- **Dependency injection**: constructor injection wired to the thing injected
- **Config keys**: where a key is defined and everywhere that reads it
- **Infra**: Terraform and Kubernetes resources
- **Docs**: doc sections linked to the symbols they govern (what `read` surfaces as *governed by*)
- **Tests**: which tests cover which code

Multiple languages can match one repo (e.g., Go backend + Angular frontend + SCSS). Each contributes its nodes and edges into a single unified graph.

## Install

### One command

```bash
uvx mcp-repo-graph install
```

This detects the AI coding agents you have installed (Claude Code, Claude Desktop,
Cursor, Windsurf, VS Code, Codex, Gemini CLI, opencode, Kiro), writes each one's
MCP config, and adds a short usage block to its instructions file so the agent
reaches for the graph before it greps. Where the agent supports it, it also grants
auto-allow so repo-graph tools don't prompt on every call.

It's safe to re-run, and `uvx mcp-repo-graph uninstall` reverses everything
(config, instructions, permissions) while leaving your graph data in place.

```bash
uvx mcp-repo-graph install --agents all          # every supported agent, not just detected
uvx mcp-repo-graph install --scope user          # your global config, not this project
uvx mcp-repo-graph install --dry-run             # show what it would write, change nothing
uvx mcp-repo-graph install --yes                 # no prompt (scripts and CI)
uvx mcp-repo-graph install --print-config cursor # print one agent's config, write nothing
```

### Manual, per client

If you'd rather wire it up yourself, the package name **is** the run command.
`uvx mcp-repo-graph` just works. No prior `pip install`, nothing to keep on
`PATH`. This is the same command VS Code, Cursor, and the MCP registry use under
the hood.

**Requirements:** Python 3.11+, and [`uv`](https://docs.astral.sh/uv/) if you use the
`uvx` path. Prebuilt wheels ship for the Rust engine on Linux (x86_64, aarch64),
macOS (Intel + Apple Silicon), and Windows (x86_64) — no Rust toolchain needed.

### Claude Code

```bash
claude mcp add repo-graph -- uvx mcp-repo-graph --repo .
```

(`--repo .` points the graph at the current project; use an absolute path to pin it.)

### VS Code

One command — adds the server to your user config:

```bash
code --add-mcp '{"name":"repo-graph","command":"uvx","args":["mcp-repo-graph","--repo","${workspaceFolder}"]}'
```

Or click **Install** on the [MCP gallery](https://code.visualstudio.com/mcp) entry,
or add it to `.vscode/mcp.json` manually (see below).

### Cursor / any MCP client — manual config

Add this to your client's MCP config (`.mcp.json`, `.cursor/mcp.json`,
`.vscode/mcp.json`, or `~/.claude.json`):

```json
{
  "mcpServers": {
    "repo-graph": {
      "command": "uvx",
      "args": ["mcp-repo-graph", "--repo", "/path/to/your/project"]
    }
  }
}
```

Prefer a persistent install? `pip install mcp-repo-graph` (or `uv tool install
mcp-repo-graph`) puts a `mcp-repo-graph` / `repo-graph` command on your `PATH`; then
use `"command": "mcp-repo-graph"` in the config above.

**`--repo` also accepts a git URL.** Point it at any public repo without cloning
first — it shallow-clones and maps it (requires `git`):

```bash
uvx mcp-repo-graph --repo https://github.com/org/repo
```

## Quick start

### 1. Initialise the target repo (optional)

```bash
uvx --from mcp-repo-graph repo-graph-init --repo /path/to/your/project
# or, if installed:  repo-graph-init --repo /path/to/your/project
```

This generates the graph, writes `.mcp.json` and CLAUDE.md instructions, and gets your
AI assistant ready to use repo-graph. If you used the one-liners above, you can skip
this — the server builds the graph on first connect.

### 2. Use it

The AI assistant now has access to all 6 tools. Example queries it can answer:

- *"What does this codebase do?"* → `orient` tool
- *"Trace the checkout flow"* → `trace` tool
- *"What would break if I change UserService?"* → `impact` tool
- *"Which nodes are relevant to this bug?"* / *"Here's a stacktrace — where do I look?"* → `find` tool
- *"Show me that function's source"* → `read` tool
- *"Give me the full graph context cheaply"* → `orient full=true`
- *"Rebuild after a big refactor"* → `refresh` tool

### 3. Freshness (automatic)

The graph stays current on its own. While the server is running it watches the repo
and does an incremental rebuild a moment after you save, so a structural question
right after an edit reflects the change with no manual `refresh`. On top of that, the
graph heals itself on cold start — if the cached `.gmap` is stale, an old format, or missing, the
engine rebuilds it and writes it back, so it's never stale when your assistant connects.

The watcher is on by default. Set `REPO_GRAPH_WATCH=0` to disable it (the cold-start
refresh still applies). It needs the `watchdog` package, which ships as a dependency.

Want the cache pre-built and committed so teammates and CI get it too? Add the
pre-commit hook automatically:

```bash
uvx mcp-repo-graph install --agents none --git-hook
```

That installs a marker-fenced `pre-commit` hook that refreshes the graph and stages
`.glia/graph/` on every commit. `uvx mcp-repo-graph uninstall` removes it again.

> **Tip:** The graph dir ignores itself (`.glia/graph/.gitignore`), so it never shows up in `git status` unless the hook stages it with `git add -f`. Skip the hook and the watcher plus cold-start refresh keep it fresh locally.

## MCP tools reference

repo-graph exposes **6 tools** — one natural verb each, backed by a Rust engine primitive.

| Tool | Parameters | Description |
|------|-----------|-------------|
| `orient` | `seed` *(optional)*, `full`, `budget` | The first call on a repo: node/edge counts, detected kinds, entry points, and a **blind-spots** note flagging which languages/edges are under-linked (so you grep those deliberately). `seed=<node>` → scoped map; `full=true` → whole-repo dense map |
| `find` | `query`, `expand`, `kind`, `top_k`, `budget` | Turn any text into the ranked nodes that matter — a symbol/keyword, or a pasted stacktrace / failing-test id / diff (resolved to the code it implicates). `expand=true` fans out to the surrounding neighbourhood. Every row carries `path:line` |
| `impact` | `nodes` *(comma-separated)*, `direction`, `depth`, `live_only`, `top_k`, `budget` | Blast radius: what a change affects (`forward`) or depends on / is used by (`backward`), as a ranked, located closure — each row with the edge `via` reason and a `⊘` when the engine finds it unreachable (likely dead). Pass several nodes for a whole-diff radius |
| `trace` | `from_node`, `to_node` *(optional)*, `depth`, `budget` | One arg: a feature end-to-end across the stack, each hop labelled with its mechanism (call / HTTP / queue / event) and cross-service hops marked. Two args: the shortest path between two nodes |
| `read` | `node` *(comma-separated)*, `context_lines`, `budget` | A node's exact source, sliced from its file by the graph's line span, plus a `context:` footer (HTTP method, cross-stack callers, covering tests, governing docs). Comma-separate to batch-read a ranked set |
| `refresh` | `repo_path` *(optional)*, `full` | Rebuild the graph (incremental by default — only changed files re-parse). `repo_path` retargets a different path or git URL; `full=true` forces a clean reparse. Routine edits are auto-picked-up by the file watcher |

Most tools also take a `budget` (max chars) so a result fits a small-model context window.

> These 6 collapsed from an earlier 13 once the engine grew answer-shaped primitives — `find`, `blast_radius`, `cross_stack_trace`, `resolve`, `coverage` — that return complete, ranked, located, live-filtered results in one call. Fewer tools = less fixed per-turn overhead and less agent confusion.

### It tells you when it doesn't know

Most tools answer an empty query with nothing, which leaves the assistant to guess whether that
means "no such edge exists" or "I couldn't see it". Since **0.5.0** an empty result comes back as a
structured *absence*: the reason, whether that reason is a **FACT** or a **HEURISTIC**, and which
extractions are partial for the mechanism that came up empty.

```
  No answer (no_edges, FACT): no carry edge touches `backend::server::server` in this graph;
  `backend::server::server` is a container: structural IMPORTS/CONTAINS/DEFINES are not carry
  edges, so seed a symbol inside it
    looked over: CALLS
    blind spots (grep to confirm):
      ⚠ CALLS (*): calls through reflection, dynamic dispatch, or higher-order indirection are
        not resolved — verify: grep the callee name
    searched 26 nodes
```

`orient` surfaces the same blind spots up front, so the model knows when to grep instead of
trusting a gap.

**What we measured.** 14 symbols across FastAPI, Gin, Hono and NestJS, each one a case where the
graph honestly has no edge but real callers exist. Same agent, same task, the only difference being
whether an empty answer explained itself. The structured absence cut cost **about 3x** on identical
tasks, in **28 of 28** matched pairs, at the same number of turns: told why the answer is empty, the
agent stops re-querying. It did **not** change correctness. Sonnet 5 answered "not safe to delete"
in all 56 runs, so if you were hoping this stops an agent deleting live code, we have no evidence of
that and some evidence against it on a careful model. Harness and raw results are in
[`bench/absence/`](bench/absence/). One model, n=14, our own harness: treat it as directional.

0.5.0 also adds whole-diff `impact` in one call (unresolved names are reported, not dropped), ranked
distinct cross-stack paths in `trace`, and role-aware labels so a declared component or service isn't
flattened to "class".

## How it works

`mcp-repo-graph` is a thin Python MCP server that wraps **glia**, a Rust engine.

1. **Parse** — per-language tree-sitter parsers extract raw nodes and unresolved references
2. **Extract** — cross-cutting extractors layer on HTTP routes, data sources, CLI entrypoints, gRPC services, queue consumers
3. **Resolve** — graph builder resolves intra-repo references; cross-graph resolvers link stacks (frontend HTTP calls → backend routes, etc.)
4. **Store** — merged graph lands in `.glia/graph/` as a zero-copy sharded `.gmap` (rkyv + mmap) plus a manifest
5. **Serve** — the MCP server loads the graph into memory and exposes the 6 tools

The Rust engine lives in its own [`glia`](https://github.com/James-Chahwan/glia) repo; `mcp-repo-graph` is the MCP-facing thin wrapper.

## Layout detection

repo-graph finds your projects itself — `go.mod`, `package.json`, `pyproject.toml`, `Cargo.toml`,
`pom.xml`, `build.gradle`, `composer.json`, `pubspec.yaml`, `mix.exs`, `Package.swift`,
`CMakeLists.txt` and friends. Point `--repo` at a monorepo root and every project under it lands in
one graph.

It also prunes on its own: `node_modules`, `vendor`, `.venv`, `site-packages`, build output
(`dist`, `target`, `.next`, `.nuxt`, `.angular`, `coverage`) and hashed bundle directories collapse
to a single region anchor instead of being parsed file by file, and `.gitignore` is honoured.

> **Note:** earlier versions documented a `config.yaml` escape hatch with `skip:` / `roots:` keys.
> That was a Python-era feature and the Rust engine does not read it — if you have one, it is being
> ignored. If auto-detection misses your layout, please
> [open an issue](https://github.com/James-Chahwan/repo-graph/issues) with the shape of the repo;
> that's more useful than a config file nobody can see.

## Graph data format

Generated files live in `.glia/graph/` inside the target repo:

- **`repo-<id>.gmap`**: the graph itself, sharded, as zero-copy rkyv (mmap'd on load)
- **`manifest.json`**: format version, repo labels, roots and parse errors, so a warm load equals a fresh generate
- **`parse_cache.bin`**: per-file content-hashed parse cache, so an incremental rebuild only re-parses edited files
- **`.gitignore`**: the dir ignores itself, so it never shows up in `git status`

The whole directory is regenerated: delete it and the next call rebuilds it.

The engine carries **36 edge categories**. The ones you'll see most: `CALLS`, `IMPORTS`,
`CONTAINS`, `DEFINES`, `USES`, `HANDLED_BY`, `HTTP_CALLS`, `IMPLEMENTS`, `INHERITS_FROM`,
`INJECTS`, `ACCESSES_DATA`, `TESTS`, `DOCUMENTS`, `NAVIGATES_TO`, plus the channel ones
(`GRPC_CALLS`, `QUEUE_FLOWS`, `WS_CONNECTS`, `EVENT_FLOWS`, `GRAPHQL_CALLS`, `RPC_CALLS`).
There are **49 node kinds**. Both tables come from the engine, so `orient` always reports the
set your version actually has.

## Privacy Policy

repo-graph runs on your machine and is built to keep your code there. Full text: [PRIVACY.md](PRIVACY.md).

- **Telemetry / analytics:** None. No tracking, no update checks, no phone-home.
- **Data collection & sharing:** None. Your source code and graph data are never sent to repo-graph, its author, or any third party.
- **Local processing & storage:** Scanning and graph-building happen locally; the graph is cached in your project's `.glia/graph/` directory and stays on your device.
- **Network access — only two cases, both user-initiated:**
  1. *Installation* — `uvx`/`pip` downloads the package and its prebuilt engine wheel from PyPI.
  2. *Git-URL targets* — if you pass a git URL to `--repo`, repo-graph runs `git clone` against the URL **you** specified; nothing is sent to repo-graph or its author. A local `--repo` path (the default) makes zero network calls.
- **Data retention:** The local cache persists until you delete it — fully under your control.
- **Contact:** [GitHub issues](https://github.com/James-Chahwan/repo-graph/issues)

## License

MIT

## Support

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