ClawMem

ClawMem is a local-first context engine/memory for AI coding agents. It indexes markdown/project documents into a SQLite-based “vault”, performs hybrid retrieval (BM25 + vector + reranking + graph/intent-based traversal), and integrates with Claude Code via hooks + an MCP stdio server and with OpenClaw via a ContextEngine plugin or MCP tools. It also captures session decisions/handoffs and writes them back to the same local vault; it includes measures against prompt injection in surfaced content and supports deduplication, lifecycle (pin/snooze/archive), and crash-safe transaction-safe indexing.

Evaluated Mar 30, 2026 (0d ago)
Repo ↗ Ai Ml ai-agent-memory rag mcp-server claude-code openclaw sqlite local-first typescript bun vector-search hybrid-search
⚙ Agent Friendliness
63
/ 100
Can an agent use this?
🔒 Security
49
/ 100
Is it safe for agents?
⚡ Reliability
42
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
65
Documentation
70
Error Messages
0
Auth Simplicity
95
Rate Limits
5

🔒 Security

TLS Enforcement
100
Auth Strength
10
Scope Granularity
20
Dep. Hygiene
55
Secret Handling
70

Local-first design with no API keys/cloud dependencies reduces exposure. However, no explicit authN/authZ is described for MCP/local tools; therefore security relies on local host trust and vault filesystem permissions. The README claims “guards against prompt injection” for surfaced content and mentions transaction-safe indexing and crash-safe behavior, which can reduce certain integrity risks. Dependency hygiene is not verifiable from provided manifest/README; scores are estimated based on explicit dependencies without CVE review.

⚡ Reliability

Uptime/SLA
0
Version Stability
55
Breaking Changes
45
Error Recovery
70
AF Security Reliability

Best When

You want an on-device, agent-integrated memory layer that can surface relevant context automatically and also provide tool-based retrieval (MCP/OpenClaw) while keeping data local in a SQLite vault.

Avoid When

You need a centralized, network-accessible API or require robust multi-user authentication/authorization at the service layer.

Use Cases

  • Persistent coding agent memory for Claude Code and OpenClaw across sessions/projects
  • Retrieval-augmented grounding over local markdown notes, docs, and research dumps
  • Session decision capture and handoff generation for long-running coding workflows
  • Targeted retrieval via MCP tools (timeline, causal links, intent search) when hooks don’t surface enough context
  • Local-only “hybrid RAG + memory graph” for privacy-sensitive developer teams

Not For

  • Use as a hosted/cloud service for remote memory (it is explicitly local/no cloud dependencies)
  • Use in environments where Bun/system dependencies cannot be installed
  • Multi-tenant server deployments without strong additional isolation controls (primarily designed for local single-user vaults)
  • Environments needing a public REST/GraphQL API for external systems (no such interface is described)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: Local stdio MCP server (no user auth described) Local plugin integration (no user auth described)
OAuth: No Scopes: No

No authentication mechanism for MCP or local tools is described; the primary security model appears to be local execution and filesystem/vault isolation.

Pricing

Free tier: No
Requires CC: No

Open-source (MIT). Costs are primarily compute/storage for local indexing and optional model servers (llama.cpp), not service pricing.

Agent Metadata

Pagination
none
Idempotent
True
Retry Guidance
Not documented

Known Gotchas

  • Designed as a local system; agents must run where the vault/models exist.
  • No authentication for MCP tools is described; in practice, ensure only trusted local clients can connect.
  • Integration modes share the same SQLite vault—concurrent access exists (WAL + busy_timeout mentioned) but agent workloads that heavily parallelize may still contend.
  • “Hooks handle 90%” suggests relying purely on MCP may miss lifecycle orchestration such as compaction and afterTurn/feedback-loop flows unless using the OpenClaw ContextEngine plugin.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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