# behavior-mcp

> behavior-mcp — putervision-behavior-mcp. Use this tool when you need to execute complex behavior trees for autonomous AI agents at high frequencies, requiring reactive priority interrupts and safety guardrails. It solves problems of deterministic action replay and efficient decision-making for AI agents, accepting behavior tree inputs and producing actionable outputs. Ideal for use cases where rapid, reliable, and safe decision-making is crucial, such as robotics, gaming, or simulation environments.

Canonical page: https://skillsregistry.net/skills/putervision-behavior-mcp  
JSON: https://api.skillsregistry.net/v1/skills/putervision-behavior-mcp

## Description

⚡ High-frequency (~60Hz) in-browser behavior tree execution engine for autonomous AI agents. Reactive priority interrupts, safety guardrails & deterministic action replay over MCP.

## Trust

- **Trust score (0–1):** 0.71
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/putervision/behavior-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "putervision-behavior-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/putervision-behavior-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/putervision-behavior-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt