MCP ConfigsMay 13, 2026·2 min read

mcp-image — MCP Image Generation & Editing Server

mcp-image is an MCP server for image generation/editing with quality presets; verified 110★ and documents `npx -y mcp-image` configs for Cursor and Claude.

Agent ready

Safe staging for this asset

This asset is staged first. The copied prompt tells the agent to inspect the staged files and ask before activating scripts, MCP config, or global config.

Stage only · 17/100Policy: stage
Agent surface
Any MCP/CLI agent
Kind
Mcp Config
Install
Stage only
Trust
Trust: Established
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Asset
Safe staging command
npx -y tokrepo@latest install e3b150c0-ca4d-54e2-a564-12206ee44e81 --target codex

Stages files first; activation requires review of the staged README and plan.

Intro

mcp-image is an MCP server for image generation/editing with quality presets; verified 110★ and documents npx -y mcp-image configs for Cursor and Claude.

Best for: Teams who want a reusable MCP image tool with per-request quality controls and saved outputs

Works with: Any MCP client (Cursor/Codex/Claude Code) + Gemini API key or OpenAI API key (provider switch)

Setup time: 6-15 minutes

Key facts (verified)

  • GitHub: 110 stars · 19 forks · pushed 2026-05-13.
  • License: MIT · owner avatar + repo URL verified via GitHub API.
  • README-backed entrypoint: npx -y mcp-image.

Main

  • Treat output paths as part of the contract: set IMAGE_OUTPUT_DIR to an absolute path so every generated image is saved and reviewable.

  • Pick a quality preset for your workflow: use fast for iteration, balanced for most work, and quality only for final deliverables (README preset table).

  • If you use OpenAI mode, keep provider env vars isolated and never commit keys; test with a single prompt first to verify permissions and output formats.

Source-backed notes

  • README documents MCP configs for Codex (~/.codex/config.toml) and Cursor (~/.cursor/mcp.json) using npx -y mcp-image.
  • README lists quality presets with a speed hint for fast (~30–40s) and env var control via IMAGE_QUALITY.
  • README includes a Claude Code setup command (claude mcp add ... -- npx -y mcp-image) and notes IMAGE_OUTPUT_DIR must be an absolute path.

FAQ

  • Do I need OpenAI to use it?: No — README says Gemini is the default provider; OpenAI is optional via IMAGE_PROVIDER=openai.
  • Where do images go?: To IMAGE_OUTPUT_DIR (absolute path) per README; the server creates the directory if missing.
  • How do I control speed vs quality?: Use presets via IMAGE_QUALITY (fast/balanced/quality) as documented in README.
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Source & Thanks

Source: https://github.com/shinpr/mcp-image > License: MIT > GitHub stars: 110 · forks: 19

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