// Agent-native memory for OpenClaw that structures memory from agent trace, execution history, decisions, tool calls, and conversations into durable long-term memory primitives.
Ambient Memori long-term memory for Claude Code via local Bash. MUST TRIGGER on essentially every non-trivial user turn: run recall before drafting any substantive response, whether or not the user mentioned memory, a prior session, or past work. The default is to check memory first; do not wait to be asked. Always fire before external lookups (WebSearch/WebFetch) and before answering any question about preferences, prior decisions, constraints, project history, status, past work, or any non-trivial coding/research task. Skip only for trivial acknowledgements/closings, purely self-contained turns where prior context cannot possibly help, or when the user explicitly opts out. Use Advanced Augmentation after drafting the final response for every non-trivial turn, as the last memory step. Use recall.summary only for broad session summaries/orientation, compaction after context loss, feedback for memory quality, quota for limits, and signup only when explicitly requested.
Use when an MCP-connected agent should use Memori tools for targeted recall, summaries, post-compaction briefs, durable memory augmentation, quota checks, signup, feedback, preferences, prior context, or cross-session continuity.
| name | memori |
| id | @memorilabs/openclaw-memori |
| description | Agent-native memory for OpenClaw that structures memory from agent trace, execution history, decisions, tool calls, and conversations into durable long-term memory primitives. |
| license | Apache-2.0 |
| homepage | https://github.com/MemoriLabs/Memori |
| repository | https://github.com/MemoriLabs/Memori.git |
| compatibility | ["openclaw"] |
| metadata | {"openclaw":{"requires":{"env":["MEMORI_API_KEY","ENTITY_ID","PROJECT_ID"],"bins":["memori"]},"primaryEnv":"MEMORI_API_KEY","externalServices":["https://api.memorilabs.ai"]}} |
Give your OpenClaw agents persistent, structured memory derived from agent execution, tool usage, workflow history, and conversations. Memori integrates seamlessly in the background via lifecycle hooks and provides agents with the tools to retrieve context when it is relevant.
Memori operates on two parallel tracks through standard OpenClaw lifecycle hooks:
After each interaction, Memori converts raw session data into structured, reusable memories asynchronously.
This is how structured memory is continuously built and updated over time. It runs after the agent responds and does not impact latency.
Recall is explicit and initiated by the agent.
Memori separates memory creation from memory recall:
Agents decide:
To maintain an efficient context window, Memori equips the agent with specific tools to retrieve history when required for the conversation:
memori_recall: Searches the structured memory graph for specific facts, constraints, and prior decisions.memori_recall_summary: Retrieves structured daily briefs and rolling summaries of prior sessions.memori_compaction: Retrieves structured post-compaction brief to continue task without interruption.memori_feedback: Reports on memory quality to improve extraction accuracy.openclaw plugins install @memorilabs/openclaw-memori
Add to your ~/.openclaw/openclaw.json or use the openclaw memori init CLI command to set up your workspace:
openclaw memori init \
--api-key "YOUR_MEMORI_API_KEY" \
--entity-id "your-entity-id" \
--project-id "your-project-id"
Alternatively, configure it directly via JSON:
{
"plugins": {
"entries": {
"openclaw-memori": {
"enabled": true,
"config": {
"apiKey": "${MEMORI_API_KEY}",
"entityId": "openclaw-user",
"projectId": "default-project"
}
}
}
}
}
memori signupWhen this plugin is active, the agent is equipped with tools to manage long-term context. The agent should use its discretion to call these tools when helpful:
memori_recall search to retrieve relevant details if context is missing regarding user preferences.memori_recall_summary tool to construct a brief if a user requests a recap.memori_signup tool to initiate the process by asking for an email address. Keys are never returned in the chat. The system securely emails the credentials to the user, who must then manually configure them to activate the plugin.memori_quota tool to check the user's current memory usage and storage limits to communicate quota status or gracefully degrade behavior if limits are reached.Check that the plugin is working and securely connected:
# Verify plugin is securely connected to the API
openclaw memori status --check
# Check for Memori logs in gateway output
openclaw gateway logs --filter "[Memori]"
Check your current API quota:
memori quota
Example output:
__ __ _
| \/ | ___ _ __ ___ ___ _ __(_)
| |\/| |/ _ \ '_ ` _ \ / _ \| '__| |
| | | | __/ | | | | | (_) | | | |
|_| |_|\___|_| |_| |_|\___/|_| |_|
perfectam memoriam
memorilabs.ai
+ Maximum # of Memories: 100
+ Current # of Memories: 0
+ You are not currently over quota.
Use this to monitor usage and upgrade if needed.
Explicit Opt-In Required: Memori requires the user to explicitly configure an API key (MEMORI_API_KEY) and an entityId. No data is captured or transmitted unless these credentials are actively provided by the user.
https://api.memorilabs.ai) only when the plugin is fully configured by the user.projectId and entityId.For details: Memori Privacy Policy
Memories persist safely across:
All storage is handled by the Memori backend and is scoped safely alongside your local MEMORY.md file without overwriting it.
Plugin not loading:
enabled: true in openclaw.jsonecho $MEMORI_API_KEYopenclaw gateway restartNo memories captured:
[Memori] errorsmemori quotaMemories not recalled:
memori_recall tool execution. If it didn't use the tool, you can prompt it to search its memory.entityId and projectId are consistent across sessions.memori quota shows count > 0.Quota exceeded:
memori quota to check usageThis skill informs the agent about the Memori plugin. The plugin must be installed separately via npm. Once installed, memory capture happens in the background, and the agent is empowered to explicitly query its memories when needed.