attestor

Zero-config memory for AI agents. No Docker. No API keys. Just install and go.

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The Problem

AI agents forget everything between sessions. Every new conversation starts from zero — no memory of what you built yesterday, what decisions you made, or what your project even does.

Built-in memory solutions (like Claude Code's MEMORY.md) store flat files that load entirely into the context window every message. No search, no ranking, no contradiction handling. As your project grows, those files become a wall of text that burns tokens without helping.

What Memwright Does

Memwright gives AI agents persistent, searchable memory that stays out of the context window until needed:

• Ranked retrieval — 3-layer search (tags + entity graph + vector similarity) returns only the most relevant memories
• Token budgets — Set a ceiling (e.g. 2,000 tokens). Memwright fits the best memories within that budget
• Contradiction handling — "User works at Google" automatically supersedes "User works at Meta"
• Namespace isolation — Multi-agent systems get isolated memory partitions per agent, user, or project
• Zero config — poetry add memwright, add one JSON block, done

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Table of Contents

• Quick Start
• Architecture
• How It Works
• MCP Tools Reference
• Retrieval Pipeline
• Python API
• Multi-Agent Support
• Cloud Backends
• Cloud Deployment
• Embedding Providers
• CLI Reference
• Configuration
• Testing
• Benchmarks
• Compatibility
• Uninstall

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Quick Start

Claude Code (one-liner)

poetry add memwright
claude mcp add memory -- memwright mcp

Restart Claude Code. Approve the server once. Done — Claude now has 8 memory tools.

Manual MCP config

Add to ~/.claude/.mcp.json (global) or .mcp.json (per-project):

{
  "mcpServers": {
    "memory": {
      "command": "memwright",
      "args": ["mcp"]
    }
  }
}

Verify

memwright doctor ~/.memwright

Or ask Claude to call memory_health. All 4 components should report healthy: SQLite, ChromaDB, NetworkX Graph, Retrieval Pipeline.

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Architecture

Component Overview