Preparing your workspace…
Preparing your workspace…
Every AI client keeps its own memory, and none of them can read the others'. These guides cover the shared context layer that fixes that — what it is, how to set it up across Claude, ChatGPT, Gemini and Cursor, and how to connect the tools your work already lives in.
Looking for a specific integration? Browse every supported app integration.
How to let ChatGPT and Claude search Gmail, Slack, Drive and Notion through a permission-aware layer that returns the source record behind every answer.
Native memory does not travel between AI clients. Here is how a shared context layer over MCP gives Claude, ChatGPT and Cursor the same facts about your work.
Conversation history, personal memory and company context are three different things. Which ones can be shared across AI clients today, and what the limits are.
A copyable context template that stops the re-briefing, where manual context files break down, and what it takes to keep the same facts current across AI tools.
Run open models on your own machine and keep what they learn: persistent memory for LM Studio, Ollama and any local MCP client. Inference stays local.
Give Cursor project-aware, persistent memory with a one-click deeplink install and a REPO workspace that auto-provisions from your repository URL.
Every AI client you use keeps its own memory. Here is how MCP gives Claude, ChatGPT, Cursor, and your other AI tools one shared, persistent memory instead.
Give Claude Desktop persistent memory it can search across sessions, using the one-click .mcpb installer, the universal installer, or a manual config file.
Step-by-step setup to connect both Claude and ChatGPT to the same memory server, so a fact stored in one is instantly searchable from the other.