AgnesAI-Labs / agnes-harness

# Agnes Harness
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### Built for trust. Made for the real world.
**Bring AI into real workflows. Turn each deployment into capabilities you can reuse.**
Quickstart · Architecture · Try the examples · Build a plugin · Documentation · MHS and devices
Developer preview (pre-alpha) · Source build · Apache-2.0
 LLM is the brain. Jev is the cerebellum. Harness is the memory. MHS is the body. 
 One foundation for enterprise FDE delivery and physical-world MHS integration. See the architecture 
Taking AI into a real deployment is rarely about the model alone. It is about the customer's systems, the people who approve the work, and the details that differ at every site. Agnes Harness (AGH) connects models, tools, task state, and business interfaces: **put the differences into plugins, let the harness run and record the work, and carry what you validated into the next deployment.**
 Read the code, ask before running a command, verify, answer, and record every step. 
 Contents 
- What AGH is, and what it is not
- Architecture: brain, cerebellum, memory and body
- What AGH does for a deployment team
- Demo videos and reproduction
- Public benchmark
- Who it is for
- Start from an example
- Run from source
- Current status
- FAQ
- Follow AGH and bring your use case
- License
## What AGH is, and what it is not
AGH is built for Forward Deployed Engineering (FDE): working in users' environments to turn systems integration, a usable interface, and ongoing iteration into delivered software. Start through CLI and Web, integrate business systems with plugins, capture task methods in Skills, and combine them into your own agent application. Explore FDE and application scenarios →
What it is not, so you can choose the right trial:
- **Not a hosted service.** AGH is a developer preview that you build from source and run in your own environment.
- **Not a sandbox for arbitrary plugin code.** Ordinary backend plugins run as trusted in-process code; approvals and the command sandbox apply to the supported execution paths. See security and trust.
- **Not a certified device driver.** MHS is AGH's own device protocol, independent of MCP. Passing its conformance suite does not certify a device as safe, and device controllers keep real-time control and physical safety.
- **Not finished.** APIs, configuration, and plugin interfaces are evolving and may change.
## Architecture: brain, cerebellum, memory and body
The brain, cerebellum, memory and body describe AGH's vision: combine reasoning, structured decisions, persistent task context, and physical capabilities. The diagram shows where each role sits in one runtime.
| Role | What it means in AGH | Current scope |
| --- | --- | --- |
| **LLM / brain** | Understand requests, reason about the task, and propose actions | Model integration through AI providers |
| **Jev / cerebellum** | Structured decisions such as routing and scoring to help coordinate execution | Integration in progress; main currently uses the built-