Giving every AI tool the same memory (Claude, ChatGPT, Cursor, Codex, Gemini)
- Published
- 09/05, 00:51
- Ingested
- 09/05, 01:00
- Source type
- Dev community
- Tier
- Community
- Source status
- Healthy
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If you're jumping between different coding tools during the day, you'll know how frustrating it can be to solve something in Claude, then hop to ChatGPT and have it not understand a thing.
The solution is to run a memory layer as an MCP server that all your tools can tap into - every time they process a request, they query the MCP for relevant context to include in the prompt, and submit any new relevant context to the MCP after the fact. Since it's implemented as an MCP, any tool that can read/write to an MCP (Claude, ChatGPT, Cursor, Codex, Gemini, etc) can understand the full context of your work without you having to painstakingly explain things.
A few things that are important to consider if you're looking to implement or evaluate one:
- Semantic search is important, since keyword matching will miss paraphrased context
- Tools should be able to define what information to share with whom
- Latency is a consideration, as this will add overhead to every request