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ourmem — Plugin Installation Guide

ourmem provides plugins for 4 AI coding platforms. Each plugin is a thin HTTP client that connects to the omem-server REST API.

Prerequisites (All Platforms)

  1. Running omem-server — Use the hosted service at api.ourmem.ai or self-host (see DEPLOY.md)
  2. API key — Create a tenant to get one: 
    # Hosted
curl -sX POST https://api.ourmem.ai/v1/tenants \
  -H "Content-Type: application/json" \
  -d '{"name": "my-workspace"}' | jq .
# → {"id": "abc-123", "api_key": "abc-123", "status": "active"}

# Self-hosted
curl -sX POST http://localhost:8080/v1/tenants \
  -H "Content-Type: application/json" \
  -d '{"name": "my-workspace"}' | jq .

1. OpenCode

Package: @ourmem/opencode Version: 0.3.0 Runtime: Bun / Node Source: plugins/opencode/

Features

Feature How it works
Auto-recall on first message Semantic search using the first user message, plus profile injection into system prompt
Keyword detection Detects "remember", "save this", "记住", "记下来", etc. and nudges the agent to use memory_store (code-block aware)
Context preservation on compaction session.compacting hook re-injects top 20 memories so context survives compaction
Privacy filtering <private> tag redaction before storage
11 tools Memory: memory_store, memory_search, memory_get, memory_update, memory_delete · Sharing: space_create, space_list, space_add_member, memory_share, memory_pull, memory_reshare

Installation

Step 1: Add to your opencode.json:

{
  "plugin": ["@ourmem/opencode"],
  "plugin_config": {
    "@ourmem/opencode": {
      "apiUrl": "https://api.ourmem.ai",
      "apiKey": "YOUR_API_KEY"
    }
  }
}

The plugin_config field is the highest priority config source. The plugin also reads ~/.config/ourmem/config.json (global) or OMEM_API_URL/OMEM_API_KEY env vars as alternatives.

Verification

# Start OpenCode — you should see 11 tools available (5 memory + 6 sharing)
opencode

# In the session, try:
# "search my memories for dark mode"
# "remember that I prefer Rust over Go"

On the first message of each session, relevant memories and your user profile are automatically injected into context.

2. Claude Code

Package: Marketplace plugin (bash hooks + skills + bundled MCP) Version: 0.3.0 Runtime: Bash 4+, curl, python3 Source: plugins/claude-code/

Features

Feature How it works
3 hooks SessionStart (load 20 recent memories), Stop (smart-ingest last conversation messages), PreCompact (save conversation before context compaction)
2 skills memory-recall (search by query), memory-store (manually save a memory)
15 MCP tools Bundled @ourmem/mcp via .mcp.json: Memory: memory_store, memory_search, memory_list, memory_ingest, memory_get, memory_update, memory_forget, memory_stats, memory_profile · Sharing: space_create, space_list, space_add_member, memory_share, memory_pull, memory_reshare
Graceful degradation If OMEM_API_KEY is not set, hooks skip silently and print setup instructions

Installation

Step 1: Configure credentials in ~/.claude/settings.json (Claude Code's native config):

{
  "env": {
    "OMEM_API_URL": "https://api.ourmem.ai",
    "OMEM_API_KEY": "YOUR_API_KEY"
  }
}

Claude Code auto-injects env fields into the process environment. This is the recommended approach.

Alternative: You can also export OMEM_API_KEY=... in your shell profile as a fallback.

Step 2: Install from the marketplace:

/plugin marketplace add ourmem/omem
/plugin install ourmem@ourmem

For local development instead:

claude --plugin-dir ./plugins/claude-code

Verification

# Start Claude Code — hooks fire automatically
claude

# Test manually:
curl -s "${OMEM_API_URL}/v1/memories?limit=5" \
  -H "X-API-Key: ${OMEM_API_KEY}" | python3 -m json.tool

On session start, recent memories are injected into context. On session end, the conversation is sent to smart-ingest for automatic memory extraction. Before context compaction, conversation messages are saved so nothing is lost.

3. OpenClaw

Package: @ourmem/ourmem Version: 0.3.0 Runtime: Node.js Source: plugins/openclaw/

Features

Feature How it works
3 hooks before_prompt_build (semantic search using prompt text), agent_end (smart-ingest with Claude content block handling), before_reset (save user messages before daily reset)
11 tools Memory: memory_store, memory_search, memory_get, memory_update, memory_delete · Sharing: space_create, space_list, space_add_member, memory_share, memory_pull, memory_reshare
ContextEngine 7 lifecycle hooks for deep integration with OpenClaw's agent loop
Claude content blocks Handles Claude's array-of-blocks content format, not just plain strings
Object export {id, name, register()} format for OpenClaw's plugin system

Installation

Step 1: Install the plugin:

openclaw plugins install @ourmem/ourmem

Step 2: Configure in openclaw.json:

{
  "plugins": {
    "entries": {
      "ourmem": {
        "apiUrl": "https://api.ourmem.ai",
        "apiKey": "YOUR_API_KEY"
      }
    }
  }
}

The plugin also reads OMEM_API_URL and OMEM_API_KEY from environment variables as fallback.

Verification

# Check plugin is installed
openclaw plugins list

# Start OpenClaw — memory tools should appear
openclaw

# The plugin automatically recalls relevant memories before each prompt
# and captures insights after each agent response

Companion Workflow: TweetClaw

OpenClaw agents can pair ourmem with TweetClaw when X/Twitter research or social automation needs durable memory. Use TweetClaw for live X/Twitter work such as search tweets, search tweet replies, follower export, user lookup, monitor tweets, webhooks, media workflows, post tweets, post tweet replies, and giveaway draws. Use ourmem to store concise decisions, selected public source URLs, campaign context, and follow-up notes.

See TweetClaw OpenClaw Memory Workflow for install, verification, credential boundaries, and a memory shape that avoids storing secrets or raw exports.

4. MCP Server

Package: @ourmem/mcp Version: 0.3.0 Runtime: Node.js (stdio transport) Source: plugins/mcp/

Features

Feature Details
15 tools Memory: memory_store, memory_search, memory_list, memory_ingest, memory_get, memory_update, memory_forget, memory_stats, memory_profile · Sharing: space_create, space_list, space_add_member, memory_share, memory_pull, memory_reshare
1 resource omem://profile (synthesized user profile)
Standard MCP Works with Cursor, VS Code Copilot, Claude Desktop, Windsurf, and any MCP-compatible client

Installation

Add to your MCP client's config file:

Cursor (.cursor/mcp.json), VS Code (.vscode/mcp.json), Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "ourmem": {
      "command": "npx",
      "args": ["-y", "@ourmem/mcp"],
      "env": {
        "OMEM_API_URL": "https://api.ourmem.ai",
        "OMEM_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Or add via CLI (Claude Desktop):

claude mcp add ourmem -- npx -y @ourmem/mcp

Verification

# Test the MCP server directly
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | \
  OMEM_API_URL=https://api.ourmem.ai \
  OMEM_API_KEY=YOUR_API_KEY \
  npx -y @ourmem/mcp

# Should return list of 15 tools

In your MCP client, you should see the ourmem tools available in the tools panel.

Troubleshooting

Common Issues

Problem Solution
Connection refused Ensure omem-server is running: curl https://api.ourmem.ai/health (or http://localhost:8080/health for self-hosted)
401 Unauthorized Check API key is correct and tenant exists
Plugin not detected Verify plugin path/installation, restart the client
No memories returned Check that memories were ingested: curl /v1/memories?limit=5 -H "X-API-Key: YOUR_KEY"
Embedding errors Check OMEM_EMBED_PROVIDER config on the server; use noop for testing
npx not found MCP server requires Node.js 18+. Install from nodejs.org

Debug Logging

Enable debug logs on the server:

RUST_LOG=debug ./omem-server

Or with Docker:

docker run -e RUST_LOG=debug -p 8080:8080 ghcr.io/ourmem/omem-server:latest

Testing API Connectivity

# Health check
curl -sf https://api.ourmem.ai/health && echo "OK" || echo "FAIL"

# Test with API key
curl -sf https://api.ourmem.ai/v1/memories?limit=1 \
  -H "X-API-Key: YOUR_API_KEY" && echo "OK" || echo "FAIL"