@cognee/cognee-openclaw

OpenClaw plugin that adds Cognee-backed memory with automatic recall and indexing.

Features

• Auto-recall: Before each agent run, searches Cognee for relevant memories and injects them as context
• Auto-index: On startup and after each agent run, syncs memory markdown files to Cognee (add new, update changed, delete removed, skip unchanged)
• CLI commands: openclaw cognee index to manually sync, openclaw cognee status to check state
• Configurable: Search type, max results, score filtering, token limits, and more

Installation

Install the plugin locally for development:

cd integrations/openclaw
npm install
npm run build
openclaw plugins install -l .

Or once published:

openclaw plugins install @cognee/cognee-openclaw

Configuration

Enable the plugin in your OpenClaw config (~/.openclaw/config.yaml or project config):

plugins:
  entries:
    cognee-openclaw:
      enabled: true
      config:
        baseUrl: "http://localhost:8000"
        apiKey: "${COGNEE_API_KEY}"
        datasetName: "my-project"
        searchType: "GRAPH_COMPLETION"
        deleteMode: "hard"
        maxResults: 6
        autoRecall: true
        autoIndex: true

Set your API key in the environment:

export COGNEE_API_KEY="your-key-here"

Configuration Options

| Option | Type | Default | Description | |--------|------|---------|-------------| | baseUrl | string | http://localhost:8000 | Cognee API base URL | | apiKey | string | $COGNEE_API_KEY | API key for authentication | | datasetName | string | openclaw | Dataset name for storing memories | | searchType | string | GRAPH_COMPLETION | Search mode: GRAPH_COMPLETION, CHUNKS, SUMMARIES | | maxResults | number | 6 | Max memories to inject per recall | | minScore | number | 0 | Minimum relevance score filter | | maxTokens | number | 512 | Token cap for recall context | | autoRecall | boolean | true | Inject memories before agent runs | | autoIndex | boolean | true | Sync memory files on startup and after agent runs | | autoCognify | boolean | true | Run cognify after new memories are added | | deleteMode | string | soft | Delete mode: soft removes raw data only, hard also removes degree-one graph nodes | | searchPrompt | string | "" | System prompt sent to Cognee to guide search query processing | | requestTimeoutMs | number | 60000 | HTTP timeout for Cognee requests | | ingestionTimeoutMs | number | 300000 | HTTP timeout for add/update (ingestion) requests, which are typically slower |

How It Works

1. On startup: Scans memory/ directory for markdown files and syncs to Cognee (add new, update changed, delete removed, skip unchanged)
2. Before agent start: Searches Cognee for memories relevant to the prompt and prepends as <cognee_memories> context
3. After agent end: Re-scans memory files and syncs any changes the agent made (including deletions)
4. State tracking:
   • ~/.openclaw/memory/cognee/datasets.json — dataset ID mapping
   • ~/.openclaw/memory/cognee/sync-index.json — per-file hash and Cognee data IDs

Memory files detected at: MEMORY.md and memory/**/*.md (recursive)

CLI Commands

# Manually sync memory files to Cognee
openclaw cognee index

# Check sync status (indexed files, pending changes)
openclaw cognee status

Development

cd integrations/openclaw
# Build once, then link for local development with an OpenClaw project
npm install
npm run build
openclaw plugins install -l .

For live rebuilds during development:

npm run dev

Testing

Run the test suite to verify functionality:

npm test