> For the complete documentation index, see [llms.txt](https://the-beacon-labs.gitbook.io/the-beacon-labs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://the-beacon-labs.gitbook.io/the-beacon-labs/getting-started/introduction.md).

# Introduction

### What is The Beacon Labs?

A task-oriented AI agent framework for digital workers and vertical AI agents.

The Beacon Labs offers a cutting-edge, enterprise-ready framework where you can orchestrate LLM calls, agents, and computer use to complete tasks cost-effectively.

It provides more reliable agents, scalability, and a task-oriented structure that you need while completing real-world cases.

## How The Beacon Labs Works

<figure><img src="/files/2rGGETxr7G9PxkXO5TCi" alt=""><figcaption></figcaption></figure>

| Component               | Description                                                      | Key Features                                                                                                                                    |
| ----------------------- | ---------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Tasks                   | The job we want to complete                                      | <p></p><ul><li>Have clear objectives</li><li>Use specific tools</li><li>Feed into larger processes</li><li>Produce actionable results</li></ul> |
| Agents                  | LLMs that use tools to complete tasks                            | <p></p><ul><li>Actions over tools</li><li>Self-reflection</li><li>Memory</li><li>Context Compression</li></ul>                                  |
| Secure Runtime          | Isolated environment to run agents                               | <p></p><ul><li>On-prem</li><li>Cloud</li><li>Customization</li></ul>                                                                            |
| Model Context Protocols | A tool standard for LLMs, supported by companies and communities | <p></p><ul><li>Wide range of tool support</li></ul>                                                                                             |

## Key Features

| Tasks                                                                                                                |
| -------------------------------------------------------------------------------------------------------------------- |
| Easily complete the tasks you need and run them in various ways to get results. Focus on the tasks, not the process. |

| Automatic Characterization                                                                                                                                    |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Share your company’s URL and objective, then input a job title for the agent. The Beacon Labs framework will generate a persona and assign tasks accordingly. |

| MCP Support                                                                                                                        |
| ---------------------------------------------------------------------------------------------------------------------------------- |
| Directly integrate with a comprehensive tool pool developed by the community and companies. Achieve stability with official tools. |

| Scalable                                                                                                                                                                                                                      |
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| The most critical components are internally positioned on the server-side, allowing you to deploy the server via Docker and perform a lightweight integration with your application on the client side in a stateless manner. |

| Direct LLM Call                                                                                                                                                                      |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| If the task you need to complete is simple and doesn’t require sub-tasks, you don’t need to spend time with agents. You can directly make an LLM call and get the results instantly. |

| Object as Response                                                                                                                                                                                        |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| When working with LLMs, getting more refined results requires programmatic responses. In this regard, you can define how you want the response by specifying it as a class and receiving it as an object. |