MCP Server for Codex CLI with Persistent Memory
Published:Jan 2, 2026 20:12
•1 min read
•r/OpenAI
Analysis
This article describes a project called Clauder, which aims to provide persistent memory for the OpenAI Codex CLI. The core problem addressed is the lack of context retention between Codex sessions, forcing users to re-explain their codebase repeatedly. Clauder solves this by storing context in a local SQLite database and automatically loading it. The article highlights the benefits, including remembering facts, searching context, and auto-loading relevant information. It also mentions compatibility with other LLM tools and provides a GitHub link for further information. The project is open-source and MIT licensed, indicating a focus on accessibility and community contribution. The solution is practical and addresses a common pain point for users of LLM-based code generation tools.
Key Takeaways
- •Clauder provides persistent memory for the OpenAI Codex CLI.
- •It stores context in a local SQLite database.
- •Features include remembering facts, searching context, and auto-loading relevant information.
- •Compatible with other LLM tools like Claude Code, OpenCode, and Gemini CLI.
- •Open-source and MIT licensed.
Reference
“The problem: Every new Codex session starts fresh. You end up re-explaining your codebase, conventions, and architectural decisions over and over.”