MemoryLayer
Semantic memory infrastructure for AI agents that actually scales.
Features
- 95% Token Savings - Retrieve only relevant memories
- Semantic Search - Find memories by meaning, not keywords
- Sub-200ms - Lightning-fast memory retrieval
- Multi-tenant - Isolated memory per agent instance
Setup
1. Sign up for FREE account
Visit https://memorylayer.clawbot.hk and sign up with Google. You'll get:
- 10,000 operations/month
- 1GB storage
- Community support
2. Configure credentials
# Option 1: Email/Password
export MEMORYLAYER_EMAIL=your@email.com
export MEMORYLAYER_PASSWORD=your_password
# Option 2: API Key (recommended for production)
export MEMORYLAYER_API_KEY=ml_your_api_key_here
3. Install Python SDK (if not using skill wrapper)
pip install memorylayer
Usage
Basic Example
// In your Clawdbot agent
const memory = require('memorylayer');
// Store a memory
await memory.remember(
'User prefers dark mode UI',
{ type: 'semantic', importance: 0.8 }
);
// Search memories
const results = await memory.search('UI preferences');
console.log(results[0].content); // "User prefers dark mode UI"
Python Example
from plugins.memorylayer import memory
# Store
memory.remember(
"Boss prefers direct reporting with zero bullshit",
memory_type="semantic",
importance=0.9
)
# Search
results = memory.recall("What are Boss's preferences?")
for r in results:
print(f"{r.relevance_score:.2f}: {r.memory.content}")
Token Savings
Before MemoryLayer:
# Inject entire memory files
context = open('MEMORY.md').read() # 10,500 tokens
prompt = f"{context}\n\nUser: What are my preferences?"
After MemoryLayer:
# Inject only relevant memories
context = memory.get_context("user preferences", limit=5) # ~500 tokens
prompt = f"{context}\n\nUser: What are my preferences?"
Result: 95% token reduction, $900/month savings at scale
API Reference
memory.remember(content, options)
Store a new memory.
Parameters:
content(string): Memory contentoptions.type(string): 'episodic' | 'semantic' | 'procedural'options.importance(number): 0.0 to 1.0options.metadata(object): Additional tags/data
Returns: Memory object with id
memory.search(query, limit)
Search memories semantically.
Parameters:
query(string): Search query (natural language)limit(number): Max results (default: 10)
Returns: Array of SearchResult objects
memory.get_context(query, limit)
Get formatted context for prompt injection.
Parameters:
query(string): What context do you need?limit(number): Max memories (default: 5)
Returns: Formatted string ready for prompt
memory.stats()
Get usage statistics.
Returns: Object with total_memories, memory_types, operations_this_month
Advanced
Memory Types
Episodic - Events and experiences
memory.remember('Deployed MemoryLayer on 2026-02-03', { type: 'episodic' });
Semantic - Facts and knowledge
memory.remember('Boss prefers concise reports', { type: 'semantic' });
Procedural - How-to and processes
memory.remember('To restart server: ssh root@... && systemctl restart...', { type: 'procedural' });
Metadata Tagging
memory.remember('User likes blue', {
type: 'semantic',
metadata: {
category: 'preferences',
subcategory: 'colors',
source: 'user_profile'
}
});
Usage Tracking
const stats = await memory.stats();
console.log(`Total memories: ${stats.total_memories}`);
console.log(`Operations this month: ${stats.operations_this_month}`);
console.log(`Plan: ${stats.plan} (${stats.operations_limit}/month)`);
Pricing
FREE Plan (Current)
- 10,000 operations/month
- 1GB storage
- Community support
Pro Plan ($99/mo)
- 1M operations/month
- 10GB storage
- Email support
- 99.9% SLA
Enterprise (Custom)
- Unlimited operations
- Unlimited storage
- Dedicated support
- Self-hosted option
- Custom SLA
Support
- Documentation: https://memorylayer.clawbot.hk/docs
- API Reference: https://memorylayer.clawbot.hk/api
- Community: Discord (link in docs)
- Issues: GitHub (link in docs)
Links
- Homepage: https://memorylayer.clawbot.hk
- Dashboard: https://dashboard.memorylayer.clawbot.hk
- API Docs: https://memorylayer.clawbot.hk/docs
- Python SDK: https://pypi.org/project/memorylayer (when published)