MemClaw for Agents

What is MemClaw

MemClaw is a persistent memory platform for AI agents. It provides semantic search, entity extraction, contradiction detection, and a knowledge graph — all accessible through 9 MCP tools over Streamable HTTP. Just connect with a URL and API key — no SDK, no plugin install.

How to Connect

Add this MCP configuration to your agent. Replace mc_YOUR_API_KEY with your real key.

{
  "mcpServers": {
    "memclaw": {
      "url": "https://memclaw.net/mcp",
      "headers": {
        "X-API-Key": "mc_YOUR_API_KEY"
      }
    }
  }
}

All 9 Tools

MemClaw exposes 9 MCP tools. Each tool is called by name with a JSON argument object.

{ "content": "Customer A uses PostgreSQL 16 in production on GKE.", "visibility": "scope_org" }

{ "items": [{"content": "Finding one"}, {"content": "Finding two", "memory_type": "fact"}], "visibility": "scope_team" }

{ "query": "PostgreSQL production setup", "top_k": 5 }

{ "query": "customer database migration status" }

{ "memory_id": "uuid-here", "content": "Updated: Customer A migrated to AlloyDB" }

{ "memory_id": "uuid-here" }

{ "entity_id": "uuid-here" }

{ "memory_id": "uuid-here", "status": "confirmed" }

{ "top_k": 5, "min_similarity": 0.5, "graph_max_hops": 2 }

Recommended System Prompt

Add this to your agent's system prompt to get optimal MemClaw usage out of the box.

You have access to MemClaw, a shared memory system for all agents.

BEFORE starting any task:
- Use memclaw_brief for a concise context briefing
- Or memclaw_search for raw results when you need full detail
- Filter by status="active" to skip archived/deleted memories

AFTER completing work:
- Store findings with memclaw_write — just provide content
- Use memclaw_write_bulk when storing multiple findings at once
- Type, weight, status, title, summary, tags are auto-inferred by LLM
- Set visibility: scope_team (default) or scope_org for cross-fleet sharing

UPDATING MEMORIES:
- Use memclaw_update to correct existing memories
- Use memclaw_transition to change status (confirmed, cancelled, outdated)
- Prefer transitioning to outdated over deleting

SEARCH TUNING:
- Use memclaw_tune to adjust your retrieval parameters
- Increase top_k for broader results, min_similarity for precision

13 Memory Types

Every memory has a type that controls its default status and freshness decay.

8 Statuses

Memories move through statuses over their lifecycle.

Common transitions:

pending → confirmed    (task completed)
pending → cancelled    (task abandoned)
active → outdated      (newer info supersedes)
active → archived      (no longer relevant)
active → conflicted    (semantic contradiction found)

Visibility Levels

Control who can read a memory with the visibility field.

Agent Trust Levels

Each agent has a trust level that determines what it can access.

Best Practices

• Search before writing to avoid duplicates.
• Use scope_team or scope_org by default to maximize knowledge sharing.
• Use memclaw_write_bulk when storing 2+ memories at once.
• Use memclaw_transition to update status — prefer outdated/archived over delete.
• Use memclaw_tune to optimize your search parameters.
• Write clear, self-contained sentences — LLM enrichment works best on well-formed content.
• Use memclaw_brief before starting tasks to get context.
• Include source_uri for provenance when available.

Quick Start

Five steps to get running with MemClaw.

{
  "mcpServers": {
    "memclaw": {
      "url": "https://memclaw.net/mcp",
      "headers": {
        "X-API-Key": "mc_YOUR_API_KEY"
      }
    }
  }
}

{ "query": "recent project updates", "top_k": 5 }

{ "content": "Deployed v2.1 to production on 2025-01-15." }

{ "query": "what do we know about the production deployment?" }