# jasper-recall

Jasper Recall v0.2.3 Local RAG (Retrieval-Augmented Generation) system for AI agent memory. Gives your agent the ability to remember and search past conversations. New in v0.2.2: Shared ChromaDB Collections — separate collections for private, shared, and learnings content. Better isolation for multi-agent setups. New in v0.2.1: Recall Server — HTTP API for Docker-isolated agents that can't run CLI directly. New in v0.2.0: Shared Agent Memory — bidirectional learning between main and sandboxed agents with privacy controls. When to Use Memory recall: Search past sessions for context before answering Continuous learning: Index daily notes and decisions for future reference Session continuity: Remember what happened across restarts Knowledge base: Build searchable documentation from your agent's experience Quick Start Setup One command installs everything:

npx jasper-recall setup

This creates: Python venv at ~/.openclaw/rag-env ChromaDB database at ~/.openclaw/chroma-db CLI scripts in ~/.local/bin/ OpenClaw plugin config in openclaw.json Why Python? The core search and embedding functionality uses Python libraries: ChromaDB — Vector database for semantic search sentence-transformers — Local embedding models (no API needed) These are the gold standard for local RAG. There are no good Node.js equivalents that work fully offline. Why a Separate Venv? The venv at ~/.openclaw/rag-env provides: BenefitWhy It MattersIsolationWon't conflict with your other Python projectsNo sudoInstalls to your home directory, no root neededClean uninstallDelete the folder and it's goneReproducibilitySame versions everywhere The dependencies are heavy (~200MB total with the embedding model), but this is a one-time download that runs entirely locally. Basic Usage Search your memory: recall "what did we decide about the API design" recall "hopeIDS patterns" --limit 10 recall "meeting notes" --json Index your files: index-digests # Index memory files into ChromaDB Create session digests: digest-sessions # Process new sessions digest-sessions --dry-run # Preview what would be processed How It Works Three Components digest-sessions — Extracts key info from session logs (topics, tools used) index-digests — Chunks and embeds markdown files into ChromaDB recall — Semantic search across your indexed memory What Gets Indexed By default, indexes files from ~/.openclaw/workspace/memory/: .md — Daily notes, MEMORY.md session-digests/.md — Session summaries repos/.md — Project documentation founder-logs/.md — Development logs (if present) Embedding Model Uses SkillBoss API Hub (/v1/pilot embedding type) for vector embeddings: Automatically routes to optimal embedding model via SkillBoss API Hub No local model download required Requires SKILLBOSS_API_KEY environment variable Agent Integration Memory-Augmented Responses

# Before answering questions about past work

results = exec("recall 'project setup decisions' --json")

# Include relevant context in your response

Automated Indexing (Heartbeat) Add to HEARTBEAT.md:

## Memory Maintenance

• New session logs? → digest-sessions
• Memory files updated? → index-digests Cron Job Schedule regular indexing: { "schedule": { "kind": "cron", "expr": "0 */6 * * *" }, "payload": { "kind": "agentTurn", "message": "Run index-digests to update the memory index" }, "sessionTarget": "isolated" } Shared Agent Memory (v0.2.0+) For multi-agent setups where sandboxed agents need access to some memories: Memory Tagging Tag entries in daily notes:

## 2026-02-05 [public] - Feature shipped

This is visible to all agents.

## 2026-02-05 [private] - Personal note

This is main agent only (default if untagged).

## 2026-02-05 [learning] - Pattern discovered

Learnings shared bidirectionally between agents. ChromaDB Collections (v0.2.2+) Memory is stored in separate collections for isolation: CollectionPurposeWho accessesprivate_memoriesMain agent's private contentMain agent onlyshared_memories[public] tagged contentSandboxed agentsagent_learningsLearnings from any agentAll agentsjasper_memoryLegacy unified (backward compat)Fallback Collection selection:

# Main agent (default) - searches private_memories

recall "api design"

# Sandboxed agents - searches shared_memories only

recall "product info" --public-only

# Search learnings only

recall "patterns" --learnings

# Search all collections (merged results)

recall "everything" --all

# Specific collection

recall "something" --collection private_memories

# Legacy mode (single collection)

recall "old way" --legacy Sandboxed Agent Access

# Sandboxed agents use --public-only

recall "product info" --public-only

# Main agent can see everything

recall "product info" Moltbook Agent Setup (v0.4.0+) For the moltbook-scanner (or any sandboxed agent), use the built-in setup:

# Configure sandboxed agent with --public-only restriction
npx jasper-recall moltbook-setup
# Verify the setup is correct
npx jasper-recall moltbook-verify

This creates: ~/bin/recall — Wrapper that forces --public-only flag shared/ — Symlink to main workspace's shared memory The sandboxed agent can then use: ~/bin/recall "query" # Automatically restricted to public memories Privacy model: Main agent tags memories as [public] or [private] in daily notes sync-shared extracts [public] content to memory/shared/ Sandboxed agents can ONLY search the shared collection Privacy Workflow

# Check for sensitive data before sharing

privacy-check "text to scan" privacy-check --file notes.md

# Extract [public] entries to shared directory

sync-shared sync-shared --dry-run # Preview first CLI Reference recall recall "query" [OPTIONS]

Options:

-n, --limit N Number of results (default: 5) --json Output as JSON -v, --verbose Show similarity scores and collection source --public-only Search shared_memories only (sandboxed agents) --learnings Search agent_learnings only --all Search all collections (merged results) --collection X Search specific collection by name --legacy Use legacy jasper_memory collection serve (v0.2.1+)

npx jasper-recall serve [OPTIONS]
Options:

--port, -p N Port to listen on (default: 3458) --host, -h H Host to bind (default: 127.0.0.1) Starts HTTP API server for Docker-isolated agents.

Endpoints:

GET /recall?q=query&limit=5 Search memories GET /health Health check

Security: public_only=true enforced by default.

Set RECALL_ALLOW_PRIVATE=true to allow private queries. Example (from Docker container):

curl "http://host.docker.internal:3458/recall?q=product+info"

privacy-check (v0.2.0+) privacy-check "text" # Scan inline text privacy-check --file X # Scan a file

Detects: emails, API keys, internal IPs, home paths, credentials.
Returns: CLEAN or list of violations.

sync-shared (v0.2.0+) sync-shared [OPTIONS]

Options:

--dry-run Preview without writing --all Process all daily notes Extracts [public] tagged entries to memory/shared/. index-digests index-digests Indexes markdown files from: ~/.openclaw/workspace/memory/.md ~/.openclaw/workspace/memory/session-digests/.md ~/.openclaw/workspace/memory/repos/.md ~/.openclaw/workspace/memory/founder-logs/.md Skips files that haven't changed (content hash check). digest-sessions digest-sessions [OPTIONS]

Options:

--dry-run Preview without writing --all Process all sessions (not just new) --recent N Process only N most recent sessions Configuration Custom Paths Set environment variables:

export RECALL_WORKSPACE=~/.openclaw/workspace
export RECALL_CHROMA_DB=~/.openclaw/chroma-db
export RECALL_SESSIONS_DIR=~/.openclaw/agents/main/sessions

Chunking Default settings in index-digests: Chunk size: 500 characters

Overlap: 100 characters

Security Considerations ⚠️ Review these settings before enabling in production: Server Binding The serve command defaults to 127.0.0.1 (localhost only). Do not use --host 0.0.0.0 unless you explicitly intend to expose the API externally and have secured it appropriately. Private Memory Access The server enforces public_only=true by default. The env var RECALL_ALLOW_PRIVATE=true bypasses this restriction. Never set this on public/shared hosts — it exposes your private memories to any client. autoRecall Plugin When autoRecall: true in the OpenClaw plugin config, memories are automatically injected before every agent message. Consider: Set publicOnly: true in plugin config for sandboxed agents Review which collections will be searched Use minScore to filter low-relevance injections What's automatically skipped (no recall triggered): Heartbeat polls (HEARTBEAT, Read HEARTBEAT.md, HEARTBEAT_OK) Messages containing NO_REPLY Messages < 10 characters Agent-to-agent messages (cron jobs, workers, spawned agents) Automated reports (📋 PR Review, 🤖 Codex Watch, ANNOUNCE_*) Messages from senders starting with agent: or worker- Safer config for untrusted contexts: "jasper-recall": { "enabled": true, "config": { "autoRecall": true, "publicOnly": true, "minScore": 0.5 } } Environment Variables The following env vars affect behavior — set them explicitly rather than relying on defaults: VariableDefaultPurposeRECALL_WORKSPACE~/.openclaw/workspaceMemory files locationRECALL_CHROMA_DB~/.openclaw/chroma-dbVector database pathRECALL_SESSIONS_DIR~/.openclaw/agents/main/sessionsSession logsRECALL_ALLOW_PRIVATEfalseServer private accessRECALL_PORT3458Server portRECALL_HOST127.0.0.1Server bind address Dry-Run First Before sharing or syncing, use dry-run options to preview what will be exposed: privacy-check --file notes.md # Scan for sensitive data sync-shared --dry-run # Preview public extraction digest-sessions --dry-run # Preview session processing Sandboxed Environments For maximum isolation, run jasper-recall in a container or dedicated account: Limits risk of accidental data exposure Separates private memory from shared contexts Recommended for multi-agent setups with untrusted agents Troubleshooting "No index found" index-digests # Create the index first "Collection not found" rm -rf ~/.openclaw/chroma-db # Clear and rebuild index-digests Model download slow First run downloads ~80MB model. Subsequent runs are instant. Links

GitHub: https://github.com/E-x-O-Entertainment-Studios-Inc/jasper-recall
npm: https://www.npmjs.com/package/jasper-recall
ClawHub: https://clawhub.ai/skills/jasper-recall