Agent memory on a budget: stretch MemoClaw's free tier before you swipe

You only get 100 paid operations before MemoClaw asks you for USDC. That sounds tight until you realize most maintenance endpoints cost nothing. If you're prototyping an OpenClaw agent, you can run for weeks on the free tier by being intentional about what hits the embeddings pipeline. MemoClaw also lives outside your prompt window. Park a memory here and it's one less token block stuffed into context, which keeps long-running builds fast and cheap.

Know which calls burn credits

MemoClaw only charges when it has to embed or run GPT-4o-mini. Everything else is free. Keep this table taped next to your console:

Operation	Endpoint	Cost	Notes
Store single memory	memoclaw store	$0.005	Paid - uses embeddings
Store batch (≤100)	memoclaw store --batch	$0.04	Paid - cheapest way to import onboarding data
Recall / semantic search	memoclaw recall	$0.005	Paid - every recall pulls semantic vectors
Context / consolidate / migrate	respective endpoints	$0.01	Paid - GPT-4o-mini + embeddings
List / get / delete / search (text)	`memoclaw list	get	delete
Stats / export / history / namespaces	{% raw %}`memoclaw stats	export	history

If an operation doesn't mention embeddings, assume it's free. Most builders still call {% raw %}store on every message instead of batching the boring stuff. Use the free APIs to audit what already exists. Lean on list/export endpoints to keep a semantic search index ready for the next session. Your context window stays empty in the process.

A frugal memory architecture

user inbox -> session summarizer (free) -> batch payload builder -> memoclaw store --batch
                    |                                       ^
                    v                                       |
             memo audit cron --------------> memoclaw stats/export (free)

1. Session summarizer: Run your OpenClaw agent's end-of-turn summary locally. Only the final summary hits MemoClaw, not the entire transcript.
2. Batch payload builder: Accumulate low-importance notes until you have ~50 entries, then call store --batch. That's $0.0008 per memory instead of $0.005.
3. Memo audit cron: Run a nightly cron that calls the free stats and export endpoints to check growth. Dedupe locally and delete junk without spending anything.

This setup burns maybe two paid calls per day: one batch store, one recall for high-signal context. Everything else rides free endpoints. Your agents still get semantic search across yesterday's work the moment they boot.

Playbook to stay under 100 calls

• Gate recalls: Cache the last recall result in your agent process. Only hit recall when the cache is empty or stale.
• Prefer keyword search first: memoclaw search "deployment" --tags infra is free. Only escalate to semantic recall if the keyword pass fails.
• Use importance scores aggressively: Drop importance to 0.2 for low-stakes memories so they rarely surface. Fewer recalls = fewer paid calls.
• Batch migrations: When importing old MEMORY.md files, chunk them into 100-line batches and pay $0.04 once instead of $0.005 × N.
• Pin reusable knowledge: Pinning doesn't cost extra but saves future recalls. Pinned items rise to the top, so one paid recall often carries the whole response.
• Share a wallet for sub-agents: Scout, fixer, and orchestrator patterns all hit the same namespace for free list/export calls. Multi-agent teams get shared persistence without multiplying costs.

When the wallet swipe is worth it

You should start paying when any of these show up:

• Team handoffs: Multiple OpenClaw agents sharing one wallet are hammering recall all day. Pay for the reliability and stop rationing calls.
• High-importance automations: If a recall miss means a production incident, $0.005 is pocket change.
• Continuous ingestion: Background workers streaming tickets or metrics should just live on the paid tier to avoid batching delays.

You still dodge the context-tax no matter what tier you're on. That's why even paid recalls feel cheap compared to stuffing 20k tokens of MEMORY.md into every prompt. MemoClaw handles persistence; you decide when the embeddings bill is worth it.

Until then, design around the free endpoints. MemoClaw's pricing is transparent. If you burn credits, it's because you chose to. Keep recalls intentional, batch the boring stores, and the 100 free calls will last longer than your prototype's runway.