# Neuron

> Neuron — recla93-neuron. Use this tool when you need to enable persistent semantic memory for AI models, allowing them to remember conversations across sessions and reinforce knowledge through vector search and Hebbian link reinforcement. It solves the problem of transient knowledge in large language models, providing a living concept graph that evolves over time. With Neuron, input conversational data and output a robust, interconnected knowledge base that can be accessed standalone or through the Gray Matter gateway.

Canonical page: https://skillsregistry.net/skills/recla93-neuron  
JSON: https://api.skillsregistry.net/v1/skills/recla93-neuron

## Description

Persistent semantic memory for AI. An MCP server that turns every conversation into a living concept graph — vector search, Hebbian link reinforcement, spreading activation — so your LLM remembers across sessions. Runs standalone or behind the Gray Matter gateway.

## Trust

- **Trust score (0–1):** 0.14
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/recla93/Neuron)

## 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": "recla93-neuron"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/recla93-neuron` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/recla93-neuron/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