# GitHub Repo to RAG (`bindler/github-repo-to-rag`) Actor

Turn any public GitHub repository into a clean dataset of code and documentation files. One download, no API token, no rate limits. Built for AI coding assistants and RAG.

- **URL**: https://apify.com/bindler/github-repo-to-rag.md
- **Developed by:** [Neil Sangwaiya](https://apify.com/bindler) (community)
- **Categories:** AI, Developer tools, Agents
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## GitHub Repo to RAG

Turn any **public GitHub repository** into a clean, structured dataset of its code and documentation. Built for AI coding assistants, codebase Q\&A bots, RAG pipelines and LLM fine-tuning.

### Why this is different

**No API token. No rate limits.** Most GitHub scrapers walk the REST API, which allows 60 requests an hour without a token, so they either crawl painfully slowly or demand you create a personal access token. This Actor downloads the repository archive in a **single request**, then extracts locally. A 50 MB repo with thousands of files costs one HTTP call.

**The noise is already removed.** Feeding a raw repo to a model wastes most of your context on things that carry no meaning: `node_modules`, `dist`, `build`, `vendor`, `__pycache__`, `.next`, coverage output, and lockfiles like `package-lock.json`, `yarn.lock`, `Cargo.lock` and `go.sum`. Minified bundles and source maps go too. All of it is excluded by default.

**Binary files can't slip through.** Extension checks alone miss binaries with text-like names, so every file is checked for null bytes before it's kept.

**Language is tagged for you**, so you can filter or chunk by language without inferring it from the extension later.

### What you get

| Field | Description |
|---|---|
| `path` | Path within the repository |
| `name` | File name |
| `extension` | File extension |
| `language` | Detected language, e.g. `typescript`, `python`, `markdown` |
| `isDocumentation` | True for `.md`, `.mdx`, `.rst`, `.txt`, `.adoc` |
| `content` | **Full file contents** |
| `lines` | Line count |
| `sizeBytes` | File size |
| `url` | Direct link to the file on GitHub |
| `repository` / `repositoryUrl` | Source repo |
| `scrapedAt` | ISO timestamp |

### Example input

Documentation only, which is usually what you want for a support or docs bot:

```json
{
  "repoUrl": "apify/crawlee",
  "includeDocs": true,
  "includeCode": false
}
```

Just TypeScript source, for a code assistant:

```json
{
  "repoUrl": "https://github.com/apify/crawlee",
  "extensions": ["ts", "tsx"],
  "excludePattern": "\\.spec\\.|\\.test\\.",
  "maxFiles": 2000
}
```

### Options

- **Repository** — full URL or `owner/repo`
- **Branch** — leave blank to try `main`, then `master`
- **Include documentation** / **Include source code** — the two common modes
- **Only these extensions** — overrides both toggles when you want something specific
- **Skip paths matching** — a regular expression against the file path, e.g. `^test/`
- **Max files** and **Max file size** — cap the run so cost is predictable, and keep generated bundles out of your corpus

### Notes

- Public repositories only. No token is used, so nothing private is accessible.
- Supported out of the box: JavaScript, TypeScript, Python, Ruby, Go, Rust, Java, Kotlin, Swift, C, C++, C#, PHP, Scala, shell, SQL, Vue, Svelte, plus YAML, TOML and JSON config.

# Actor input Schema

## `repoUrl` (type: `string`):

A public GitHub repository. Full URL or owner/repo, e.g. https://github.com/apify/crawlee or apify/crawlee.

## `branch` (type: `string`):

Leave blank to try main then master.

## `includeDocs` (type: `boolean`):

Markdown, MDX, reStructuredText, plain text and AsciiDoc.

## `includeCode` (type: `boolean`):

Common source and config file types.

## `extensions` (type: `array`):

Optional. Overrides the two toggles above. Example: md, ts, py

## `excludePattern` (type: `string`):

Optional regular expression against the file path. Example: ^test/|.spec.

## `maxFiles` (type: `integer`):

Stop after this many files. Controls your cost.

## `maxFileKb` (type: `integer`):

Skip files larger than this. Keeps generated bundles out of your corpus.

## Actor input object example

```json
{
  "repoUrl": "https://github.com/apify/crawlee",
  "includeDocs": true,
  "includeCode": true,
  "maxFiles": 1000,
  "maxFileKb": 200
}
```

# Actor output Schema

## `files` (type: `string`):

One record per file with full content, path, language and line count.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "repoUrl": "https://github.com/apify/crawlee"
};

// Run the Actor and wait for it to finish
const run = await client.actor("bindler/github-repo-to-rag").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "repoUrl": "https://github.com/apify/crawlee" }

# Run the Actor and wait for it to finish
run = client.actor("bindler/github-repo-to-rag").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "repoUrl": "https://github.com/apify/crawlee"
}' |
apify call bindler/github-repo-to-rag --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bindler/github-repo-to-rag"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/1gQalwbtIiQaCOgOB/builds/VMrB5gQuoi5L0QxEg/openapi.json