MemoClaw vs AgentMemory — focused memory service vs bundled toolkit
If you’re building AI agents that need persistent memory, you’ve probably seen both MemoClaw and AgentMemory. Both solve the “my agent forgets everything between sessions” problem. Both offer cloud-hosted memory with semantic search. But they take different approaches.
MemoClaw does memory and nothing else. AgentMemory bundles memory with VPN proxying and web search into one platform.
Here’s what I found comparing them side by side.
Different bets on what agents need
MemoClaw treats memory as a hard problem that deserves its own service. Store, recall, consolidate, extract, relate, traverse — everything is about making your agent’s memory actually useful.
AgentMemory treats agents as needing multiple capabilities from one provider. Memory, proxy/VPN for web requests, and web search in a single CLI and API.
Neither approach is wrong. It depends on what you’re building.
Feature comparison
Here’s what each platform offers for the memory portion, since that’s the core overlap:
Memory basics
| Feature | MemoClaw | AgentMemory |
|---|---|---|
| Store & recall | ✅ | ✅ |
| Semantic search | ✅ | ✅ |
| Full-text search | ✅ (free) | Not documented |
| Importance scoring | ✅ (0-1 scale) | ❌ |
| Tags | ✅ | Not documented |
| Namespaces | ✅ | ❌ (per-agent isolation) |
| Batch operations | ✅ (up to 100) | ❌ |
Advanced memory features
| Feature | MemoClaw | AgentMemory |
|---|---|---|
| Memory relations | ✅ (5 types, free) | ❌ |
| Knowledge graph traversal | ✅ (free) | ❌ |
| Immutable memories | ✅ | ❌ |
| Consolidation | ✅ ($0.01) | ❌ |
| Extract (conversation → facts) | ✅ ($0.01) | ❌ |
| Context assembly | ✅ ($0.01) | ❌ |
| Markdown migration | ✅ ($0.01) | ❌ |
| Core (pinned) memories | ✅ (free) | ❌ |
| Memory history/versioning | ✅ (free) | ❌ |
| Export | ✅ (free) | ✅ (Pro+) |
Beyond memory
| Feature | MemoClaw | AgentMemory |
|---|---|---|
| VPN/Proxy | ❌ | ✅ |
| Web search | ❌ | ✅ |
| File storage (photos, docs) | ❌ | ✅ (up to 100MB/file) |
| Secrets vault | ❌ | ✅ |
| End-to-end encryption | ❌ | ✅ |
This is where AgentMemory’s generalist model shows. If your agent needs proxied web requests or web search, AgentMemory has that built in.
Pricing
This is the biggest architectural difference between the two.
MemoClaw uses x402 pay-per-request pricing. No accounts, no subscriptions, no API keys. Your EVM wallet address is your identity. 100 free calls, then pay per request with USDC on Base.
| Operation | Cost |
|---|---|
| Store | $0.005 |
| Recall (semantic) | $0.005 |
| Batch store (100 memories) | $0.04 |
| Consolidate/Extract/Context | $0.01 |
| List, delete, relations, graph, export | Free |
AgentMemory uses tiered subscriptions:
| Tier | Storage | Agents | Proxy requests | Price |
|---|---|---|---|---|
| Free | 100GB | 1 | 500/mo | $0 |
| Pro | 500GB | 3 | 25K/mo | Paid (not public) |
| Team | 2TB | 10 | 250K/mo | Paid (not public) |
| Enterprise | Unlimited | Unlimited | Unlimited | Custom |
The cost math depends on how you use it:
- Low volume (a few recalls per day): both free tiers cover you.
- Medium volume (hundreds of calls/day): MemoClaw costs add up. AgentMemory Pro might be cheaper if you’d also use the proxy.
- Multi-agent teams: MemoClaw’s single-wallet model means all agents share one memory pool at no extra cost. AgentMemory charges per agent.
Authentication
MemoClaw uses wallet-based identity. No signup, no API keys. Your EVM wallet address authenticates every request via x402. Great for crypto-native users, eliminates credential management. But you need a wallet.
AgentMemory uses traditional API key auth with sign-up. Familiar pattern, but another set of credentials to manage.
Developer experience
Both have CLIs:
# MemoClaw
npm install -g memoclaw
memoclaw init # set up wallet
memoclaw store "..." # store a memory
memoclaw recall "..." # semantic search
# AgentMemory
npm install -g agentmemory-cli
agentmemory init # set up API key
agentmemory store "..."
agentmemory search "..."MemoClaw also has an MCP server (memoclaw-mcp) for tool-based access from Claude Desktop, Cursor, or any MCP client. For OpenClaw users, there’s a dedicated ClawHub skill and hooks integration.
AgentMemory’s CLI includes agentmemory proxy get <url> for proxied HTTP requests, which is useful if your agent fetches web content.
When MemoClaw makes more sense
- You need memory depth: consolidation, relations, knowledge graphs, immutable memories, importance scoring
- You’re using OpenClaw — first-class hooks and ClawHub skill
- You want pay-per-use with no subscriptions
- You’re crypto-native and wallet-based auth fits your stack
- You run multi-agent teams — shared wallet = shared memory, no per-agent fees
- You’re migrating from MEMORY.md files
When AgentMemory makes more sense
- You need memory + proxy + web search from one vendor
- Your agent scrapes or fetches web data regularly
- You want to store files alongside text memories
- You need end-to-end encryption
- You prefer API key auth over wallet-based identity
- Raw storage volume matters more than memory features
Using both
They’re not mutually exclusive. A reasonable setup:
- MemoClaw for intelligent memory (preferences, decisions, corrections with relations and importance scoring)
- AgentMemory for proxied web requests and file storage
The overlap is smaller than it looks.
Wrapping up
MemoClaw goes deep on memory. AgentMemory goes wide on agent infrastructure. If your agent’s main challenge is remembering things well — understanding context, tracking contradictions, consolidating knowledge — MemoClaw’s feature set is hard to match. If your agent needs a broader set of cloud services bundled together, AgentMemory covers more ground.
For OpenClaw users, MemoClaw is the natural fit. The hooks integration means your agent gets persistent memory with a few commands and zero code changes.
Try MemoClaw: Quickstart — store and recall in under 2 minutes | OpenClaw Hooks — automatic memory for your agent | Pricing
Try AgentMemory: agentmemory.cloud