OpenClaw Memory MCP Server

Automatically records AI conversation turns and code changes to local Markdown.

README.md

OpenClaw Memory

Your AI conversations disappear after every session. OpenClaw Memory fixes that.

Every time you chat with an AI coding assistant, valuable context — decisions, solutions, debugging steps — vanishes when the session ends. The next session starts from zero.

OpenClaw Memory automatically records every conversation turn to local Markdown files, making your entire AI chat history searchable and browsable. No cloud, no database — just plain text files in your project.

How It Works

You chat with AI  →  Every turn auto-saved to .openclaw_memory/journal/2026-02-24.md
                  →  Search past conversations via MCP tool or web viewer

Each journal entry captures the complete conversation: timestamps, model used, your input, the AI's full response, and any code changes made.

Quick Start

1. Install

pip install claw-memory

2. Initialize in your project

cd your-project
claw-memory init

This creates:

  • .openclaw_memory/journal/ — where chat history lives
  • .cursor/mcp.json — connects the MCP server to Cursor
  • .cursor/rules/memory.mdc — tells the AI agent to auto-record

3. Restart Cursor — that's it. Every conversation is now being recorded.

Searching Past Conversations

The AI agent can search your history automatically. Just ask naturally:

"We discussed this before, what was the solution?"

"Last time we fixed a similar bug, how did we do it?"

The agent will call memory_search() behind the scenes and find matching conversations.

Search via Web Viewer

# Single project (current directory)
claw-memory web

# Multiple projects — scan a parent directory
claw-memory web --scan-dir ~/projects

Opens a browser-based viewer where you can:

  • Browse journal files by date
  • Full-text search across all conversations
  • Dark/light mode
  • Multi-project view: use --scan-dir to scan a parent directory and browse all projects in one place, with sidebar grouped by project

What Gets Recorded

Each conversation turn is saved as Markdown:

## 14:32 | claude-4-opus

### User

How do I fix the N+1 query problem in the user list endpoint?

### Agent

The issue is in `api/users.py` where each user triggers a separate query for their roles...

### Code Changes

- `api/users.py` (modified)
- `tests/test_users.py` (modified)

MCP Tools

Tool Purpose
memory_log_conversation Record a complete conversation turn
memory_log_conversation_append Append to the last turn (for long responses)
memory_search Search chat history by keyword

Storage

All data is stored locally in .openclaw_memory/journal/ as plain Markdown files — one file per day. No database, no cloud sync. You own your data.

The .openclaw_memory/ directory is auto-gitignored to prevent accidental commits of chat history.

Project Isolation

Each project gets its own .openclaw_memory/ directory. MCP tools always operate on the current project only.

To view multiple projects together, use the web viewer with --scan-dir.

License

Apache 2.0

Tools 3

memory_log_conversationRecord a complete conversation turn
memory_log_conversation_appendAppend to the last turn (for long responses)
memory_searchSearch chat history by keyword

Try it

Search my past conversations for the solution we found for the N+1 query problem.
Find the last time we discussed refactoring the user authentication module.
What was the specific debugging step we took to fix the API timeout error last week?

Frequently Asked Questions

What are the key features of OpenClaw Memory?

Auto-saves every conversation turn to local Markdown files. Captures timestamps, model used, user input, AI responses, and code changes. Provides a web-based viewer for full-text search and browsing history. Supports multi-project scanning to view history across different directories. Maintains project isolation with local .openclaw_memory directories.

What can I use OpenClaw Memory for?

Developers needing to recall specific debugging steps from previous sessions. Teams maintaining context across long-term coding projects. Users who want to own their AI chat history without relying on cloud storage.

How do I install OpenClaw Memory?

Install OpenClaw Memory by running: pip install claw-memory

What MCP clients work with OpenClaw Memory?

OpenClaw Memory works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep OpenClaw Memory docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Open Conare