OpenClaw

OpenClaw is a personal AI assistant that runs locally and supports 11+ messaging platforms (WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Teams, Matrix, Zalo, etc.). AutoMem integrates with OpenClaw through three setup modes, in recommended order:

1. plugin — native OpenClaw plugin with typed AutoMem tools and auto-recall
2. mcp — mcporter-based setup with the same typed tools
3. skill — legacy curl fallback

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Integration Modes

Aspect	Plugin (recommended)	MCP	Skill (legacy)
Protocol	Native plugin HTTP client	MCP over stdio (mcporter)	Direct HTTP via curl
Tool interface	Typed tools (automem_store_memory, etc.)	Same typed tools via mcporter	Raw curl commands
Auto-recall	Built-in hook, DM-only by default	Via skill rules	Via skill rules
Dependencies	OpenClaw plugin system	Node.js + mcporter	bash + curl
Config location	plugins.entries.automem	skills.entries.automem + mcporter.json	skills.entries.automem

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Architecture

Plugin mode (recommended)

graph LR
    subgraph "Messaging Platforms"
        WA["WhatsApp"]
        TG["Telegram"]
        SL["Slack"]
        DC["Discord"]
        OT["Signal, iMessage, Teams, etc."]
    end

    subgraph "OpenClaw"
        OC["OpenClaw Gateway"]
        PL["AutoMem Plugin"]
    end

    AM["AutoMem API<br/>FalkorDB + Qdrant"]

    WA --> OC
    TG --> OC
    SL --> OC
    DC --> OC
    OT --> OC

    OC --> PL
    PL -->|"HTTP client"| AM

MCP mode architecture

OpenClaw skill → mcporter → mcp-automem stdio server → AutoMem HTTP API

Skill mode architecture (legacy)

OpenClaw skill → curl → AutoMem HTTP API

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Installation

Plugin mode (recommended)

npx @verygoodplugins/mcp-automem openclaw --mode plugin

MCP mode

npx @verygoodplugins/mcp-automem openclaw --mode mcp --workspace ~/clawd

Legacy skill mode

npx @verygoodplugins/mcp-automem openclaw --mode skill --workspace ~/clawd

Common options

npx @verygoodplugins/mcp-automem openclaw --dry-run  # Preview without writing

CLI Options

Option	Description	Default
--mode <plugin|mcp|skill>	Integration mode	plugin
--scope <workspace|shared>	Install scope for mcp/skill modes	workspace
--workspace <path>	OpenClaw workspace directory	Auto-detected
--endpoint <url>	AutoMem service endpoint	http://127.0.0.1:8001
--api-key <key>	AutoMem API key	None (optional)
--plugin-source <spec>	npm spec or local path for plugin installs	@verygoodplugins/mcp-automem
--name <name>	Project name for memory tags	Auto-detected
--dry-run	Preview changes without modifying files	Off
--quiet	Suppress non-error output	Off

What the installer does

Plugin mode:

1. Installs the package as an OpenClaw plugin
2. Configures plugins.entries.automem in openclaw.json
3. Archives old skill overrides that would shadow the plugin-shipped skill
4. Cleans up legacy AGENTS.md blocks from previous installs

MCP mode:

1. Installs the automem skill to <workspace>/skills/automem/SKILL.md
2. Creates <workspace>/config/mcporter.json with the automem server entry
3. Stores endpoint/API key in skills.entries.automem (secrets stay out of mcporter.json)

Skill mode (legacy):

1. Installs the curl-based automem skill to <workspace>/skills/automem/SKILL.md
2. Configures skills.entries.automem.env with endpoint and API key

Workspace Detection

The installer searches for the workspace in this order:

1. --workspace flag (explicit)
2. OPENCLAW_WORKSPACE or CLAWDBOT_WORKSPACE environment variable
3. ~/.openclaw/openclaw.json config file (reads agents.defaults.workspace)
4. Default paths: ~/.openclaw/workspace, ~/clawd, ~/.clawdbot/workspace

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Plugin Configuration

In plugin mode, the installer writes to ~/.openclaw/openclaw.json under plugins.entries.automem:

{
  "plugins": {
    "entries": {
      "automem": {
        "enabled": true,
        "config": {
          "endpoint": "http://127.0.0.1:8001",
          "apiKey": "your-token-here",
          "autoRecall": true,
          "autoRecallLimit": 3,
          "exposure": "dm-only",
          "defaultTags": ["platform/openclaw", "project/my-project"]
        }
      }
    }
  }
}

Config fields

Field	Type	Default	Description
endpoint	string	—	Base URL for the AutoMem service (required)
apiKey	string	—	Bearer token for authenticated deployments (optional)
autoRecall	boolean	true	Recall relevant memories before each agent turn
autoRecallLimit	integer	3	Max memories to auto-recall (1–10)
exposure	string	"dm-only"	Auto-recall scope: dm-only, all, or off
defaultTags	string[]	[]	Tags applied when the request doesn’t supply tags

MCP/Skill configuration

In MCP and skill modes, the installer writes to skills.entries.automem instead:

{
  "skills": {
    "entries": {
      "automem": {
        "enabled": true,
        "env": {
          "AUTOMEM_ENDPOINT": "http://127.0.0.1:8001",
          "AUTOMEM_API_KEY": "your-token-here"
        }
      }
    }
  }
}

Note

The installer handles JSON5-style comments in OpenClaw config files (single-line //, block /* */, trailing commas) using a string-aware comment stripper that preserves URLs containing //.

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Natural Language Mappings

In plugin and MCP modes, the skill maps natural language to typed AutoMem tools:

User says	Tool called
”remember …” or “store this”	automem_store_memory
”what do you know about …” or “recall …”	automem_recall_memory
”update memory …”	automem_update_memory
”delete memory …”	automem_delete_memory (recalls first if ambiguous)
“link these memories …”	automem_associate_memories
”is memory healthy?”	automem_check_health

Slash commands also work: /automem remember ..., /automem recall ..., /automem update ..., /automem delete ....

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Memory Operations (Legacy Skill)

In legacy skill mode, the bot constructs curl commands directly:

Store a memory:

curl -s -X POST "$AUTOMEM_ENDPOINT/memory" \
  -H "Content-Type: application/json" \
  ${AUTOMEM_API_KEY:+-H "Authorization: Bearer $AUTOMEM_API_KEY"} \
  -d '{
    "content": "Brief title. Context and details. Impact/outcome.",
    "tags": ["openclaw"],
    "importance": 0.7
  }'

Recall memories:

curl -s \
  ${AUTOMEM_API_KEY:+-H "Authorization: Bearer $AUTOMEM_API_KEY"} \
  "$AUTOMEM_ENDPOINT/recall?query=your+search+query&limit=5"

Update a memory:

curl -s -X PATCH "$AUTOMEM_ENDPOINT/memory/MEMORY_ID" \
  -H "Content-Type: application/json" \
  ${AUTOMEM_API_KEY:+-H "Authorization: Bearer $AUTOMEM_API_KEY"} \
  -d '{"content":"Updated context."}'

Delete a memory:

curl -s -X DELETE "$AUTOMEM_ENDPOINT/memory/MEMORY_ID" \
  ${AUTOMEM_API_KEY:+-H "Authorization: Bearer $AUTOMEM_API_KEY"}

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Behavioral Rules

Session Start — Recall First

The skill (or plugin auto-recall hook) recalls at session start for:

• Questions about past decisions, preferences, or history
• Debugging or troubleshooting (search for similar past issues)
• Project planning or architecture discussions

Skip recall for:

• Simple greetings or small talk
• Questions answerable from general knowledge
• Direct file operations or commands

Storage Importance Levels

Category	Importance	Examples
Decisions	0.9	”Chose Railway over Fly.io for deployment. Reason: persistent volumes.”
User corrections	0.8	”Human prefers dark mode themes. Corrected my light mode suggestion.”
Bug fixes	0.8	”WhatsApp webhook failing. Root cause: expired token. Solution: auto-refresh.”
Preferences	0.7	”Human likes terse responses, no fluff.”
Patterns	0.7	”Use early returns for validation in all API routes.”
Context	0.5	”Set up new Telegram channel for family group.”

Tags

Tags use namespace-style formatting:

• platform/openclaw — automatically added
• project/<name> — derived from project name (auto-detected or --name flag)

Memory Layers

OpenClaw uses four complementary memory layers:

Layer	Storage	Purpose	Scope
Daily files (memory/YYYY-MM-DD.md)	Local filesystem	Raw session logs	Single workspace
MEMORY.md / workspace notes	Local filesystem	Curated local notes	Single workspace
memory-core	OpenClaw file memory tools	Fast file-backed retrieval	Single workspace
AutoMem	FalkorDB + Qdrant	Semantic graph memory	Cross-session, cross-platform

memory-core is complementary — AutoMem does not replace it. Use memory-core for local file-backed notes and AutoMem for the semantic cross-session layer.

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Error Handling

• If AutoMem is unavailable: Continue normally — memory enhances but never blocks
• Do not announce failures to the human
• Fall back to file-based memory (memory/ directory and MEMORY.md)
• Only check /health endpoint to diagnose persistent failures

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Troubleshooting

Plugin not taking effect

1. Run openclaw plugins list — verify automem appears
2. Restart the OpenClaw gateway after installation
3. Check ~/.openclaw/openclaw.json for plugins.entries.automem

MCP tools missing

1. Run mcporter list — verify automem server appears
2. Check <workspace>/config/mcporter.json contains the automem server
3. Confirm skills.entries.automem.env.AUTOMEM_ENDPOINT is set in ~/.openclaw/openclaw.json

Legacy skill not connecting

1. Verify endpoint: curl "$AUTOMEM_ENDPOINT/health"
2. Check API key if using an authenticated instance
3. Check firewall/VPN for Railway endpoints
4. Consider switching to plugin or mcp mode for a better experience

Bot mentions “Memory Tools Disabled”

This refers to OpenClaw’s built-in memory-lancedb plugin, not AutoMem. The AutoMem skill explicitly instructs the bot to ignore this message — AutoMem handles embeddings server-side with no client API keys required.

Quick verification commands

Mode	Command
Plugin	openclaw plugins list
MCP	mcporter list
Skill	openclaw skills info automem

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Comparison with MCP Integrations

Feature	Plugin	MCP	Skill (legacy)	MCP Platforms
Protocol	Native plugin HTTP	MCP over stdio	REST via curl	MCP over stdio
Setup	Single CLI command	CLI + mcporter	CLI only	CLI + config
Runtime deps	OpenClaw plugin system	Node.js + mcporter	bash + curl	Node.js
Auto-recall	Built-in hook	Skill rules	Skill rules	Platform-dependent
Error recovery	Plugin error handling	MCP error protocol	curl exit codes	MCP error protocol
Auth	Plugin config	Environment variables	HTTP Bearer token	Environment variables