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

Quick Start

Setup

One command installs everything:

npx jasper-recall setup

This creates:

Why Python?

The core search and embedding functionality uses Python libraries:

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:

| Benefit | Why It Matters | |---------|----------------| | Isolation | Won't conflict with your other Python projects | | No sudo | Installs to your home directory, no root needed | | Clean uninstall | Delete the folder and it's gone | | Reproducibility | Same 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

1. digest-sessions — Extracts key info from session logs (topics, tools used) 2. index-digests — Chunks and embeds markdown files into ChromaDB 3. recall — Semantic search across your indexed memory

What Gets Indexed

By default, indexes files from ~/.openclaw/workspace/memory/:

Embedding Model

Uses sentence-transformers/all-MiniLM-L6-v2:

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:

| Collection | Purpose | Who accesses | |------------|---------|--------------| | private_memories | Main agent's private content | Main agent only | | shared_memories | [public] tagged content | Sandboxed agents | | agent_learnings | Learnings from any agent | All agents | | jasper_memory | Legacy 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:

The sandboxed agent can then use:

~/bin/recall "query"  # Automatically restricted to public memories

Privacy model: 1. Main agent tags memories as [public] or [private] in daily notes 2. sync-shared extracts [public] content to memory/shared/ 3. 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:

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:

What's automatically skipped (no recall triggered):

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:

| Variable | Default | Purpose | |----------|---------|---------| | RECALL_WORKSPACE | ~/.openclaw/workspace | Memory files location | | RECALL_CHROMA_DB | ~/.openclaw/chroma-db | Vector database path | | RECALL_SESSIONS_DIR | ~/.openclaw/agents/main/sessions | Session logs | | RECALL_ALLOW_PRIVATE | false | Server private access | | RECALL_PORT | 3458 | Server port | | RECALL_HOST | 127.0.0.1 | Server 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:

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

Setup

One command installs everything:

npx jasper-recall setup

This creates:

Why Python?

The core search and embedding functionality uses Python libraries:

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:

| Benefit | Why It Matters | |---------|----------------| | Isolation | Won't conflict with your other Python projects | | No sudo | Installs to your home directory, no root needed | | Clean uninstall | Delete the folder and it's gone | | Reproducibility | Same 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

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:

"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.