Export ChatGPT history to OpenClaw memory system

A Reddit post details a method for exporting ChatGPT conversation history and importing it into OpenClaw's memory system, allowing local AI agents to access years of accumulated context.
Process steps
The method involves five main steps:
- Data Request: Request a Data Export from ChatGPT settings. The download link may take hours to a day to arrive.
- Cleanup: Extract the downloaded zip file and keep only conversation data files (named
conversations--xxx.jsonor starting withconversations). Delete extra files likeuser.jsonandmodel_comparisons.json. - Converter Setup: Use the
ai-chat-md-exporttool to convert JSON files to Markdown. Install globally via npm:npm install -g ai-chat-md-export - Batch Conversion: Run conversion commands from the terminal in the folder containing JSON files:
Windows (CMD):
Linux and Mac:mkdir output_md for /r %f in (*.json) do ai-chat-md-export -i "%f" -p chatgpt -o ./output_md/mkdir -p output_md find . -name "*.json" -exec ai-chat-md-export -i {} -p chatgpt -o ./output_md/ \; - Data Transfer: Upload the generated Markdown files to the OpenClaw server using SCP:
Replace the IP address and username with your specific setup.scp -r output_md/*.md [email protected]:~/.openclaw/workspace/memory/openai/
Once files are placed in the openai memory folder, OpenClaw can index them, providing the agent with long-term memory of historical conversations. The post notes this process also works for Claude history.
📖 Read the full source: r/openclaw
👀 See Also

How OpenCLAW Memory Actually Works: Fixing Agent 'Forgetting'
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How 40 Prompt Revisions Turned Claude AI Summaries Into a Product: A Tutoring Platform Case Study ($19K MRR)
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Upgrading an NVMe Raspberry Pi 5 to OpenClaw 9.3 Using a Staged Clone
A developer upgraded a production NVMe Raspberry Pi 5 from OpenClaw 2026v7.1-2 to 9.3 by cloning to a spare Pi, wiping the original, and restoring — with the agent SSHing in to do the work.

Using Claude to analyze writing patterns for better custom instructions
A Reddit user describes a method for creating more effective custom instructions by having Claude analyze 10 writing samples to identify concrete patterns like punctuation avoidance and analogy sources, rather than relying on subjective tone descriptions.