gemini_chatLABSCO SUMMARY
Grounded search, images, SVG and video — the four things worth reaching to another model for.
Search grounding is the quiet one: answers come from a Google search run at question time rather than from a training cutoff, with the sources attached. SVG output is the underrated one, because it returns editable vector code instead of a raster you have to redo. Two limits to plan around: deep research takes minutes, so keep max_iterations to 3 or 4 under Claude Desktop's 4-minute tool timeout and push it higher in an IDE; and media resolution is a real cost dial, with MEDIA_RESOLUTION_MEDIUM giving the same OCR quality as high at half the tokens.
What it is
A TypeScript server that puts Google's Gemini models behind MCP tools — chat with Google Search grounding, image and video generation, SVG output, and image analysis — with results previewing inline rather than landing as file paths.
What you get
- gemini_chat — answers with Google Search grounding on by default, sources returned as markdown links, and a thinking_level you can raise or lower
- gemini_deep_research — repeated grounded searches synthesised into a report, steered with focus_areas and bounded by max_iterations
- generate_image — image generation with optional search grounding, so a chart can be drawn from current data; full resolution saved to disk
- edit_image — natural-language edits with multi-turn continuity through thought signatures
- generate_svg — real SVG code in technical, artistic, minimal or data-viz styles, ready to commit or embed
- generate_video — Veo 3.1 video with native synchronised audio, aspect ratio, seed and up to 4 variations per call
- describe_image and analyze_image — a fast description, or structured extraction and detailed reasoning
- load_image_from_path — a local file read in as base64 for any of the image tools
- generate_landing_page — a self-contained HTML page with inline CSS and vanilla JS
- gemini_prompt_assistant, gemini_list_models and gemini_help — prompting guidance, the live model list, and documentation without leaving the client
Requirements
A Gemini API key from Google AI Studio in GEMINI_API_KEY — the free tier covers most development use, with rate limits showing up first on deep research. Node.js 18 or higher; run with npx from @houtini/gemini-mcp. Optional: GEMINI_IMAGE_OUTPUT_DIR to auto-save generated images and video, and ffmpeg on PATH for video thumbnails.
Setup effort
One command plus a key — npx -y @houtini/gemini-mcp, then supply credentials
USE CASES
01
Answering a question about something that changed this month
Grounded chat searches Google first and returns the sources, instead of answering from training data.
02
Getting a diagram you can actually edit
Generate it as SVG in the technical style and commit the code, rather than exporting a picture.
03
Illustrating a point with real current numbers
Turn on search when generating the image so the chart is drawn from data fetched at that moment.
04
Producing a short video with sound
Veo generates a few seconds with synchronised audio and polls until it is ready — no separate render step.
05
Reading a screenshot you have on disk
Load the file as base64, then describe it quickly or analyse it in detail depending on what you need.
06
Cutting the token cost of bulk image work
Drop media resolution to low for simple passes; for PDF text extraction, medium reads the same as high.
13 tools
Listed in project docs. Your client may show a different list.
gemini_deep_researchgemini_list_modelsgemini_helpgemini_prompt_assistantgenerate_imageedit_imagedescribe_imageanalyze_imageload_image_from_pathgenerate_videogenerate_svggenerate_landing_pageBEFORE YOU INSTALL
What to know first
Tools you get
13 tools named in the project's documentation.
Requires
- npx on PATH
- Node.js 18+
- GEMINI_API_KEY in your environment
Where it runs
Both documented clients run the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
npx -y @houtini/gemini-mcpMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"gemini": {
"command": "npx",
"args": [
"@houtini/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>"
}
}
}
}Claude Code
CLAUDE CODE · TERMINAL
claude mcp add -e GEMINI_API_KEY=<YOUR_GEMINI_API_KEY> -s user gemini -- npx -y @houtini/gemini-mcp
