# longmem

> Use this tool when you need to unify and search across project knowledge, leveraging hybrid semantic and keyword memory to streamline information retrieval. It solves problems of fragmented project data and facilitates collaboration with features like integration with Cursor, Claude Code, and team access. Ideal for use in multi-project environments where centralized knowledge management is crucial.

Canonical page: https://skillsregistry.net/skills/marerem-longmem  
JSON: https://api.skillsregistry.net/v1/skills/marerem-longmem

## Description

Hybrid semantic + keyword memory across all your projects. Works with Cursor, Claude Code, and your team.

## Trust

- **Trust score (0–1):** 0.76
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ju9a8ugaxd)
- **Repository:** <https://github.com/marerem/longmem>

## 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": "marerem-longmem"
    }
  }
}
```

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