# hybrid-ai-mcp

> hybrid-ai-mcp — angrysky56-hybrid-ai-mcp. Use this tool when you need to explain and inspect complex decision-making processes in AI systems, bridging the "black box" problem by creating a transparent and formal decision layer. It solves problems of interpretability and accountability in AI models, particularly when leveraging neural network perception. Input includes neural network outputs and decision logic, producing human-interpretable decision traces as output.

Canonical page: https://skillsregistry.net/skills/angrysky56-hybrid-ai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/angrysky56-hybrid-ai-mcp

## Description

Bridges the "black box" problem by creating a formal, inspectable decision layer. Each decision traces to explicit logical operations - no hidden states. Leverage NN perception while maintaining human-interpretable decision logic.

## Trust

- **Trust score (0–1):** 0.94
- **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/angrysky56/hybrid-ai-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": "angrysky56-hybrid-ai-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/angrysky56-hybrid-ai-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/angrysky56-hybrid-ai-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