MemoryRouter
Gemini CLI memory

Gemini CLI memory: context files, and where the context ends

Gemini CLI is generous with context files and refreshingly scriptable. Memory between runs still means files, because that is what a stateless CLI has.

Google. Sources checked 2026-09-25.

How Gemini CLI handles memory today

Gemini CLI uses GEMINI.md context files with hierarchical loading: global from the home directory, project root, and subdirectories, so instructions follow the directory tree. It also supports MCP servers, which is how external tools and memory providers plug in.

Context files are instructions. They are loaded fresh every run and carry no record of previous sessions unless a human maintains that record by hand.

What Gemini CLI forgets

A fresh process every run means a fresh memory every run.

The fix with MemoryRouter

Gemini CLI supports MCP servers. Point it at MemoryRouter and the CLI gets recall and store tools over a vault shared with your other tools.

  1. 1

    Add the server to your Gemini CLI settings

    Register the remote MCP endpoint in the CLI MCP settings file. The transport is streamable HTTP with OAuth.

    Gemini CLI settings.json

    {
      "mcpServers": {
        "memoryrouter": {
          "httpUrl": "https://mcp.memoryrouter.ai/mcp"
        }
      }
    }
  2. 2

    Authenticate and select a vault

    The CLI walks you through the OAuth flow on first use.

  3. 3

    Ask for memory explicitly at first

    Tool calls are model-directed. Prompt with "check memoryrouter for the decisions about this module" until it becomes a habit.

Start a MemoryRouter vault

Works with Gemini CLI over MCP and with every other tool you connect. 14-day free trial.

Related

Gemini CLI memory FAQ

Sources

Sources checked 2026-09-25. Tool behavior changes; check the vendor docs before relying on a detail.

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