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Gemini CLI is Google’s terminal-based AI coding assistant. it supports MCP servers, so you can connect screenpipe to give Gemini context about what you’ve been working on.

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setup

Gemini CLI uses MCP for external tools. add screenpipe to your config: 
# add screenpipe MCP server
gemini config mcp add screenpipe "npx -y screenpipe-mcp"
or edit your config file directly: 
{
  "mcpServers": {
    "screenpipe": {
      "command": "npx",
      "args": ["-y", "screenpipe-mcp"]
    }
  }
}
restart Gemini CLI after configuration.

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usage

once configured, Gemini can search your screen history: 
gemini

> what was I working on this morning?

> find the error message I saw in my terminal earlier

> summarize the documentation I was reading about kubernetes

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available tools

screenpipe provides these MCP tools to Gemini:
  • search-content - search screen OCR, audio transcriptions
  • search-ui-events - search accessibility data: keyboard input, mouse clicks, app switches, clipboard (macOS)
  • get-ui-event-stats - get aggregated UI event statistics by app
  • export-video - create video exports from screen recordings

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example workflows

context-aware coding: 
> I was looking at a react component earlier that handled
> form validation, find it and help me implement something similar
debug from memory: 
> there was an error in my build output, find it and help me fix it
recall documentation: 
> what did that API documentation say about rate limits?

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requirements

  • screenpipe running on localhost:3030
  • Gemini CLI installed
  • Node.js >= 18.0.0