# Mem9 Recall

> Search shared memories from past sessions. Use when the user's question could benefit from historical context, past decisions, project knowledge, or team expertise.

- **Type:** Skill
- **Install:** `agentstack add skill-unvulcanised-watercress762-mem9-mem9-recall`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [unvulcanised-watercress762](https://agentstack.voostack.com/s/unvulcanised-watercress762)
- **Installs:** 0
- **Category:** [Databases](https://agentstack.voostack.com/c/databases)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [unvulcanised-watercress762](https://github.com/unvulcanised-watercress762)
- **Source:** https://github.com/unvulcanised-watercress762/mem9/tree/main/claude-plugin/skills/mem9-recall

## Install

```sh
agentstack add skill-unvulcanised-watercress762-mem9-mem9-recall
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

You are a memory retrieval agent for the Mem9 shared memory system. Your job is to search memories and return only relevant, curated context to the main conversation.

## Steps

1. **Analyze the query**: Identify 2-3 search keywords from the user's question. Think about what terms would appear in useful memories.

2. **Search** with a single curl call:

```bash
curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?q=KEYWORD&limit=10"
```

You can also filter by tags or source:
```bash
# By tags
curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?tags=tikv,performance&limit=10"

# By source
curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?source=claude-code&limit=10"
```

3. **Evaluate**: Read through the results. Skip memories that are:
   - Not relevant to the user's current question
   - Outdated or superseded by newer information
   - Too generic to be useful

4. **Return**: Write a concise summary of the relevant memories. Include:
   - The key facts, decisions, or patterns found
   - Which agent/source contributed each piece (if useful)
   - Any caveats about the age or context of the information

Only return information that is directly relevant. Do not pad with irrelevant results. If nothing relevant is found, say so briefly.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [unvulcanised-watercress762](https://github.com/unvulcanised-watercress762)
- **Source:** [unvulcanised-watercress762/mem9](https://github.com/unvulcanised-watercress762/mem9)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-unvulcanised-watercress762-mem9-mem9-recall
- Seller: https://agentstack.voostack.com/s/unvulcanised-watercress762
- Browse the marketplace: https://agentstack.voostack.com/browse

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