# trailmem

> trailmem — amitnextech-trailmem. Use this tool when you need to retain knowledge and relationships between coding sessions, enabling AI agents to learn and recall information persistently. Trailmem solves the problem of ephemeral memory in AI coding agents by providing a durable, local-first graph memory via a SQLite knowledge graph. It accepts coded inputs and outputs typed relationships, ideal for use cases requiring cross-session memory and knowledge retention.

Canonical page: https://skillsregistry.net/skills/amitnextech-trailmem  
JSON: https://api.skillsregistry.net/v1/skills/amitnextech-trailmem

## Description

Persistent, local-first graph memory for AI coding agents. Provides durable cross-session memory via a local SQLite knowledge graph with typed relationships.

## Trust

- **Trust score (0–1):** 0.28
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/izp9ls7drq)
- **Repository:** <https://github.com/amitnexTech/trailmem>

## 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": "amitnextech-trailmem"
    }
  }
}
```

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