# engram-synapse

> engram-synapse — 000erick-engram-synapse. Use this tool when you need to perform semantic vector searches on Engram memory, enabling efficient information retrieval and pattern matching. It solves problems related to data discovery, similarity search, and knowledge retrieval, particularly in applications with large amounts of semantic data. The tool accepts vectorized queries as input and returns relevant results, making it ideal for use cases that require intelligent search and recommendation systems.

Canonical page: https://skillsregistry.net/skills/000erick-engram-synapse  
JSON: https://api.skillsregistry.net/v1/skills/000erick-engram-synapse

## Description

Semantic vector search for Engram memory — pure Go, zero CGO, MCP-native. Formerly 000Erick/synapse.

## 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/000Erick/engram-synapse)

## 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": "000erick-engram-synapse"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/000erick-engram-synapse` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/000erick-engram-synapse/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