# GitHub Repo Codebase Packer: LLM Context & Tokens (`laborious_rumor/github-repo-codebase-llm-packer`) Actor

Pack GitHub repositories, source files, and docs into clean LLM-ready context with token counting, path filtering, and file tree visualization.

- **URL**: https://apify.com/laborious_rumor/github-repo-codebase-llm-packer.md
- **Developed by:** [Lakshay Papneja](https://apify.com/laborious_rumor) (community)
- **Categories:** Developer tools, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 packed codebase files

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## GitHub Repo Codebase Packer: LLM Context & Tokens (v1.0)

Pack entire GitHub repositories, documentation folders, and source trees into a single, clean **LLM-ready context prompt** formatted for Claude 3.5 Sonnet, ChatGPT, DeepSeek, and Cursor.

Built for AI engineers, autonomous coding agents, and developers who need to feed full multi-file codebases into LLMs without copy-pasting hundreds of individual files.

***

### ⚡ Key Capabilities

- **Automated Git Tree Traversal**: Recursively scans full GitHub repository trees via official GitHub tree endpoints.
- **Token Estimation**: Pre-computes estimated token counts per file (`Math.ceil(chars / 3.8)`) and for the entire assembled prompt.
- **Smart Path & Lockfile Filtering**: Automatically ignores `node_modules`, `.git`, build output (`dist/`, `build/`), and lockfiles (`package-lock.json`, `pnpm-lock.yaml`) to conserve token limits.
- **Extension Targeting**: Filter specifically by language (e.g. `.ts`, `.py`, `.go`, `.rs`, `.md`).
- **Dual Outputs**:
  1. **Default Dataset**: Every file as an individual record with metadata, token counts, and source code.
  2. **`LLM_PROMPT.md` in Key-Value Store**: Ready-to-copy markdown document featuring an ASCII file tree and fenced code blocks.

***

### ⚙️ Input Parameters

| Field | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `repoUrls` | `array` | `["https://github.com/expressjs/express"]` | List of GitHub repository URLs or `owner/repo` strings. |
| `branch` | `string` | `""` | Target branch or tag (defaults to repo default). |
| `extensions` | `array` | `[".js", ".ts", ".py", ...]` | Allowed extensions to include in prompt. |
| `maxFileSizeKb` | `integer` | `100` | Max file size in KB to prevent huge bundle files from polluting context. |
| `maxFiles` | `integer` | `150` | Maximum source files to extract (up to 1,000). |
| `excludePaths` | `array` | `["node_modules", ".git", ...]` | Directories or paths to exclude. |

***

### 📦 Sample Dataset Output

```json
{
  "repo": "expressjs/express",
  "path": "lib/express.js",
  "extension": ".js",
  "sizeBytes": 3240,
  "linesCount": 112,
  "estimatedTokens": 850,
  "rawUrl": "https://raw.githubusercontent.com/expressjs/express/master/lib/express.js",
  "scrapedAt": "2026-10-31T20:56:00.000Z"
}
```

# Actor input Schema

## `repoUrls` (type: `array`):

List of GitHub repo URLs or 'owner/repo' strings to pack (e.g. https://github.com/expressjs/express or vercel/ai).

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

Specific Git branch or tag. Leave empty to use repository default branch.

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

File extensions to include in LLM context.

## `maxFileSizeKb` (type: `integer`):

Skip individual files larger than this size in KB to conserve token context.

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

Maximum source files to include in output prompt and dataset (up to 1,000).

## `excludePaths` (type: `array`):

Directories, filenames, or globs to ignore.

## Actor input object example

```json
{
  "repoUrls": [
    "https://github.com/expressjs/express"
  ],
  "branch": "",
  "extensions": [
    ".js",
    ".ts",
    ".py",
    ".go",
    ".rs",
    ".md",
    ".json",
    ".yaml",
    ".html",
    ".css"
  ],
  "maxFileSizeKb": 100,
  "maxFiles": 150,
  "excludePaths": [
    "node_modules",
    ".git",
    "dist",
    "build",
    "coverage",
    "vendor",
    ".next",
    "package-lock.json",
    "yarn.lock",
    "pnpm-lock.yaml"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("laborious_rumor/github-repo-codebase-llm-packer").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("laborious_rumor/github-repo-codebase-llm-packer").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 '{}' |
apify call laborious_rumor/github-repo-codebase-llm-packer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,laborious_rumor/github-repo-codebase-llm-packer"
        }
    }
}
```

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/9R1mD3M8b1kbyNItP/builds/htKDc3eb7ib7gO5Ar/openapi.json