Character.AI → Gemini: Migrate Your AI Memory (2026 Method)

Character.AI has no official export to Gemini. You'll copy each character's Definition (Greeting, Persona, Scenario, Example dialogues) from the character editor and rebuild them as Gems with the Definition pasted into Gem instructions, worldbuilding files stored in Google Drive for native pull, and archived chats added as referenced files. Plan 25–45 minutes per character. A shared MCP-based memory layer like MemoryLake lets you keep canonical character memory in one place.

Three drivers in 2026:

• Long-context worldbuilding. Gemini handles long lore documents well.
• Bundled access. Gemini is included with Google One or Workspace for many users.
• Native Drive pull. Worldbuilding documents in Drive load live without re-attaching.

Different surfaces.

Character.AI memory lives inside each Character: its Definition (Greeting, Description, Persona, Scenario, Example dialogues), the user Persona, and per-character chat history.

Gemini memory spans Saved Info (short snippets, account-wide), Gems (custom personas with their own instructions and optional referenced files), and Past Chats / Activity (governed by Activity controls).

A character usually becomes a Gem reading from a Drive folder. The Definition becomes Gem instructions. User Persona becomes a Saved Info entry.

Character.AI does not offer a one-click export.

1. Open each character in the editor. Copy Greeting, Description, Persona, Scenario, and Example dialogues into a text file per character.
2. Capture your user Persona. Account settings → Persona.
3. Archive key chats. Copy salient turns into a markdown file.
4. Gather worldbuilding documents. Collect originals.

End state: one folder per character with definition.txt, archived chats, and worldbuilding files; plus a single persona.txt.

Gemini lands the import via Drive plus Gems.

1. Create a Drive folder per character. Upload worldbuilding files (PDF, DOCX, Markdown) into the folder.
2. Create a Gem per character. Open Gem Manager → New Gem. Name it after the character.
3. Paste the Definition into the Gem's instructions. Add an explicit line telling Gemini which Drive folder holds canon lore.
4. Add user Persona to Saved Info. Gemini settings → Saved Info → Add.
5. Validate. Open the Gem and run a representative scene to confirm context.

Gemini reads Drive content live, so updates to the uploaded lore propagate without re-creating the Gem.

• In-platform community. Character.AI's discovery feed and shared characters stay on the original platform.
• Hidden per-character memory. Platform-side behaviors don't transfer.
• Content policy differences. Gemini's policies differ from Character.AI's; some roleplay patterns won't work. Test first.
• Ongoing sync. New chats on Character.AI next week won't appear in Gemini unless you redo the export.

If you want characters portable across many AIs, per-tool drift becomes its own job.

MemoryLake holds canonical character definitions, worldbuilding lore, and persona files once and exposes them through MCP. Gemini integrations can read the same MemoryLake project through a Workspace add-on or external integration calling its REST endpoint.

• One source of truth. Update once; every connected AI sees the change.
• Standard file formats. PDFs, Word, Excel, PowerPoint, Markdown, and images live in MemoryLake's Document Drive as-is.
• Drop-in for the next AI. Add Claude or ChatGPT with a config change.

Step 1: Create a project and load your context

Sign in to MemoryLake, open Project Management, and click Create Project. Name it after the character. Drag worldbuilding lore and images (PDF, Markdown, images) into the Document Drive under My Space, then open the Documents Tab and click Add Documents. Paste the character's Definition, your user Persona, and archived chat highlights into the Memories Tab via Add Memory.

Step 2: Generate an MCP Server endpoint

Open the MCP Servers Tab inside the project, click Add MCP Server, describe it (e.g., "Shared character memory"), and click Generate. MemoryLake returns a Key ID, a Secret, and an Endpoint URL. Copy the Secret immediately — it is shown only once.

Step 3: Point Gemini at the endpoint

Run a Workspace add-on or external integration that calls the REST endpoint with the Bearer token and injects the returned context into the Gem's instructions or the opening prompt of a session.