AgentMemo#

Persistent memory and human approval for any AI agent — one API, any model, MCP-native.

⚠️ What This Skill Does#

This skill connects your agent to the AgentMemo cloud API ( api.agentmemo.net) to store and retrieve memories and request human approvals. Your agent's memory content is sent to and stored on AgentMemo's servers.

• Requires: A free API key from agentmemo.net — set as AGENTMEMO_API_KEY in your OpenClaw environment
• Data: Memory content you store is sent to api.agentmemo.net over HTTPS. You own your data and can delete it at any time.
• Optional: The agentmemo-mcp npm package is only needed for MCP client setups (Claude Desktop, Cursor, etc.) — not required for REST/SDK use
• No data sharing: AgentMemo does not share your data with third parties. See privacy policy.

If you prefer fully local memory, this skill is not for you. If you're comfortable with a cloud API (like you'd use for any other SaaS tool), read on.

---

AgentMemo solves the two biggest pain points of autonomous AI agents:

1. Amnesia — agents forget everything between sessions. No more starting from zero.
2. Dead ends — agents need to pause and ask a human before sensitive actions. Now they can.

Features#

• 🧠 Persistent memory — store, search, and retrieve memories across sessions
• ✅ Human approval gateway — agents pause, humans approve/reject, agents resume
• 🔌 MCP-native — one-line setup in Claude, Cursor, Windsurf, OpenClaw, or any MCP client
• 🌐 Works with any model — REST API, store in Claude, recall in GPT, use in local Llama
• 📦 npm SDK — npm install agentmemo for TypeScript/JavaScript projects
• 🆓 Free tier — 10K memories, 100 searches/day, no credit card needed

Quick Start#

Get your free API key#

Sign up at agentmemo.net → free tier, instant access.

Option 1: MCP (Claude / Cursor / OpenClaw)#

Add to your MCP config ( claude_desktop_config.json or equivalent):

json

{
  "mcpServers": {
    "agentmemo": {
      "command": "npx",
      "args": ["agentmemo-mcp"],
      "env": {
        "AGENTMEMO_API_KEY": "your_api_key_here"
      }
    }
  }
}

That's it. Your agent now has remember, recall, forget, request_approval, and check_approval tools.

Option 2: OpenClaw (this skill)#

Set your API key in OpenClaw config or workspace env:

bash

AGENTMEMO_API_KEY=am_your_key_here
AGENTMEMO_API_URL=https://api.agentmemo.net

Then reference this skill in your agent instructions — see Usage below.

Option 3: REST API directly#

bash

# Store a memory
curl -X POST https://api.agentmemo.net/memories \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"content": "User prefers dark mode and compact layouts", "namespace": "preferences"}'

# Search memories
curl "https://api.agentmemo.net/memories/search?q=user+preferences&namespace=preferences" \
  -H "X-API-Key: YOUR_KEY"

# Request human approval
curl -X POST https://api.agentmemo.net/approve \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"action": "Send email to client@example.com", "context": "Draft is ready for review"}'

Option 4: TypeScript/JavaScript SDK#

bash

npm install agentmemo

typescript

import AgentMemo from 'agentmemo';

const memo = new AgentMemo({ apiKey: process.env.AGENTMEMO_API_KEY });

// Store a memory
await memo.memories.store({
  content: 'Project deadline is March 31st',
  namespace: 'project-alpha'
});

// Search memories
const results = await memo.memories.search('deadline', { namespace: 'project-alpha' });

// Request human approval
const approval = await memo.approvals.request({
  action: 'Delete 500 old log files',
  context: 'Freeing up 2GB disk space'
});

Usage (as an OpenClaw skill)#

When this skill is active, use AgentMemo to:

Store memories#

Save important context that should persist across sessions:

text

Remember: [something worth keeping]
Namespace: [project/user/agent — optional, default is "default"]

Use POST /memories with your AGENTMEMO_API_KEY.

Search memories#

Before starting any task, search for relevant prior context:

text

Recall: [what you're looking for]

Use GET /memories/search?q=QUERY&namespace=NAMESPACE.

Request approval#

Before any sensitive or irreversible action, request human approval:

text

Request approval for: [action description]
Context: [why this needs doing]

Use POST /approve. Poll GET /approve/:id or set a callback_url webhook.

API Reference#

Base URL: https://api.agentmemo.net

Auth: X-API-Key: YOUR_KEY header on all requests.

MethodEndpointDescriptionPOST``/memoriesStore a memoryGET``/memories/searchSemantic search across memoriesGET``/memories/:idRetrieve memory by IDDELETE``/memories/:idDelete a memoryGET``/usageCheck usage stats and limitsPOST``/approveSubmit action for human approvalGET``/approve/:idPoll approval status

POST /memories#

json

{
  "content": "string (required)",
  "namespace": "string (optional, default: 'default')",
  "metadata": {}
}

Returns { id, namespace, content, metadata, created_at }.

GET /memories/search#

Query params: q (required), namespace (optional), limit (optional, max 50).

Returns { query, namespace, count, results: [{ id, content, score, metadata, created_at }] }.

POST /approve#

json

{
  "action": "string (required) — what the agent wants to do",
  "context": "string (optional) — background/reasoning",
  "callback_url": "string (optional) — webhook for decision notification"
}

Returns { id, status: 'pending', ... }.

GET /approve/:id#

Returns { id, status: 'pending'|'approved'|'rejected', decision_at, ... }.

MCP Tools#

When using the MCP server ( npx agentmemo-mcp), your agent gets these tools:

ToolDescriptionrememberStore a memoryrecallSearch stored memoriesforgetDelete a memory by IDlist_memoriesList recent memories in a namespacerequest_approvalSubmit action for human reviewcheck_approvalPoll approval status

Pricing#

PlanPriceMemoriesSearches/dayFree$010,000100Starter$19/mo250,0001,000Pro$99/mo2,000,00010,000Team$499/moUnlimitedUnlimited

Links#

• 🌐 Website: agentmemo.net
• 📦 npm (MCP): npmjs.com/package/agentmemo-mcp
• 📦 npm (SDK): npmjs.com/package/agentmemo
• 🐙 GitHub: github.com/andrewpetecoleman-cloud/agentmemo
• 📧 Support: hello@agentmemo.net