Home › Getting Started

Getting Started

Work through the steps in order, and you will experience the basics end to end — from your first sign-in to saving a memory from your AI, recalling it, and confirming it on the dashboard.

Time required: about 10 minutes · What you need: a Google or GitHub account, and an MCP-capable AI service (Claude, ChatGPT, Cursor, Gemini, Codex, etc.)

1 Sign in

Open memory.kagura-ai.com and the sign-in screen appears.

  1. Choose "Continue with Google" or "Continue with GitHub".
  2. Check "I agree to the Terms of Service and Privacy Policy".
  3. Approve on the provider's authentication screen, and your workspace dashboard opens.

The Trial plan is invite-based. See the pricing page for current sign-up availability.

2 Connect your AI service

You use Kagura AI as a shared memory from the AI service you already work with. Open "API keys" or "OAuth apps" in the left menu to reach the "Credentials & Integrations" screen, where you find your connection credentials and the MCP connection URL (MCP endpoint) shared by all clients.

There are two ways to connect — pick the one that matches your AI service.

Option A: connect with an API key (programmatic access — Claude Code, Python SDK, etc.)

  1. On the "API keys" tab, issue a new API key. It is shown only once, so copy and save it.
  2. In your tool's MCP (connector) settings, set the MCP connection URL and the key you saved.
  3. Once connected, your AI can use the remember and recall tools.

Option B: connect with an OAuth app (desktop / web clients — Claude Desktop, ChatGPT)

  1. On the "OAuth apps" tab, create the OAuth app for your service (one for Claude, one for ChatGPT).
  2. Add the MCP connection URL to Claude Desktop's or ChatGPT's connector (MCP server) settings.
  3. When you connect, a Kagura AI sign-in screen opens; approve it, and your AI can use the remember and recall tools.

3 Save a memory from your AI service (remember)

In a conversation with your connected AI, simply ask it to remember what matters.

The AI calls remember and saves it, with a summary and tags, into a context — a "container" for memories. Keeping one context per project or theme makes things easier to find later (you can ask your AI: "Create a new context called 'Reading notes'").

"Remember this design decision, with the reasoning." / "Remember the conclusions from today's meeting."

4 Recall it from your AI service (recall)

Open a new conversation and try recalling what you just saved.

The AI searches the context with recall and pulls in only the relevant memories. No more re-explaining from scratch across conversations and tools.

"Recall how we decided this before." / "Review this with last week's discussion in mind."

5 Confirm it on the dashboard

Check in the web interface that your memories were saved. Go back to memory.kagura-ai.com and use the menu on the left.

  1. Dashboard — if total memories and API calls have grown, your AI service is connected and working. You can also see the memory-creation timeline.
  2. Contexts — shows each context's memory count and last activity. What you saved in step 3 appears here.
  3. Storage — check how much of your storage you are using.

6 Use it as a team

Everything you just did can be shared with your team as is. Invite members to your workspace and give each a role (owner / admin / member / viewer).

Each context has a visibility setting (private / shared / public), so shared team knowledge and personal memories stay cleanly separated. Save your team's decisions into a shared context, and every member gets the same knowledge — from whichever AI service they ask.