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meigenai-mcp

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Meigen AI MCP Server

Meigen AI | Curated Meigen AI Prompts & Instant Generator

MCP Badge License: MIT Node Zero Config MCP Read Only

A Model Context Protocol server that exposes the canonical Meigen AI knowledge surface — image generation workflows and styles, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://meigenai.online

🎨 About Meigen AI

Meigen AI is a curated prompt gallery combined with an inline image generator, built for creators who want to go from inspiration to rendered output in a single step. The site hosts over 5,000 prompts collected from working creators, each paired with the actual image it produced. Visitors can browse by category, copy any prompt, translate it into one of 60+ languages, and run it through a built-in generation dock without switching tabs. The default engine is GPT Image 2, and users can swap to Flux, Nano Banana, Google Gemini, or Seedream depending on style preference or engine-specific syntax. New users receive 30 starter credits to test generation immediately, and browsing and copying prompts is free with no account required.

Related MCP server: Muse AI Image MCP Server

Key Features

  • 5,000+ curated prompts with rendered previews — every entry shows the literal prompt text alongside the image it produced, so users see the output before committing to a run.

  • One-tap in-page generation — a persistent generator dock lets users run, tweak, and re-run prompts without leaving the gallery page.

  • Multi-engine support — GPT Image 2, Flux, Nano Banana, Google Gemini, and Seedream are all available; prompts are tagged with the engine they were authored for.

  • 60+ language translation — prompt translation preserves technical parameters such as aspect ratios, style tokens, and trigger words rather than doing a plain text translation.

  • 20+ category filters — Portrait, Cinematic, 3D, Product, Cyberpunk, and more, with a sticky category navigation bar for fast browsing.

  • Weekly trending updates — new prompts are sourced from X, Reddit, Xiaohongshu, and Discord, keeping the library current with what creators are actually shipping.

Use Cases

  • A product photographer searches the "Product" category, finds a studio-lighting prompt that matches a client brief, translates it to adjust locale-specific style tokens, and generates a test render in under two minutes.

  • A concept artist browsing the "Cyberpunk" filter copies five prompts, runs them through Flux for its color grading, and compares outputs side by side to pick a direction before opening their main tool.

  • A brand director who does not write prompts natively uses the gallery as a starting library, copying and lightly editing prompts rather than building from scratch.

  • A developer building a prompt-dependent feature uses the site to validate which phrasing patterns produce consistent outputs across engines before hardcoding anything.

  • An illustrator tracks weekly trending prompts to stay aware of emerging aesthetics without spending time on social media research themselves.

Who Is It For

Meigen AI is aimed at anyone whose work involves AI image generation but who spends too much time searching for prompts that actually work. The primary users are content creators, product photographers, concept artists, and brand-focused designers who need reliable output quickly. It is also useful for developers and founders who want to test image generation behavior across multiple engines without building their own prompt libraries from scratch. The site assumes no prior knowledge of prompt engineering — the gallery provides working examples, and the translation and generation tools handle the technical layer — making it accessible to both experienced practitioners and people just starting with AI image tools.

Tools

list_styles

Return the canonical list of image-generation styles or presets the site exposes. (Meigen AI)

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for Meigen AI.

Input: no parameters. Returns: text/markdown.

get_official_links

Return the canonical list of official links for Meigen AI (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://meigenai/styles — Supported image-generation styles and presets.

  • site://meigenai/pricing — Canonical pricing entry point.

  • site://meigenai/faq — Short FAQ generated from public site metadata.

  • site://meigenai/links — Canonical URLs to share with users.

Prompts

tell_me_about_meigenai

Summarize what the site is, who it's for, and how it works. — Meigen AI

try_image_style_meigenai

Recommend a starting image-generation style for a stated goal. — Meigen AI

Installation

Install via Smithery

npx -y @smithery/cli install meigenai-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

git clone https://github.com/rocnubie/meigenai-mcp.git
cd meigenai-mcp
pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{
  "mcpServers": {
    "meigenai-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/meigenai-mcp/src/index.mjs"
      ]
    }
  }
}

Debug with MCP Inspector

npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

Available Tools

3 tools
get_pricingA

Return the canonical pricing entry point for Meigen AI.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It simply states 'Return' without detailing behavior (e.g., data source, caching, side effects). The agent lacks insight into whether this is a simple fetch, requires authentication, or has latency implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no unnecessary words. It is front-loaded with the action verb 'Return', providing immediate clarity. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters, no output schema, and no annotations, the description is minimally adequate. However, it could add context about the return format or entry point structure to help the agent anticipate the response. As is, it leaves some uncertainty.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema coverage is 100% (trivially). The description adds no parameter information because none are needed. Baseline for 0 parameters is 4, and the description meets this adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Return' and clearly identifies the resource as 'the canonical pricing entry point for Meigen AI'. It effectively distinguishes the tool from its siblings (list_styles, get_official_links) which focus on different aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or cases where another tool might be preferred. The description only states what it does, not when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_stylesA

Return the canonical list of image-generation styles or presets the site exposes. (Meigen AI)

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the burden. It states the tool returns a list, implying a read operation. However, it does not explicitly say it is read-only or disclose any behavioral traits (e.g., rate limits, idempotency).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with the key information. Every word is necessary and concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and zero params, the description is minimal. It says 'canonical list' but does not specify the format or structure of the returned list. For a simple tool, it is adequate but lacks some detail about what the list contains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are 0 parameters, and schema coverage is 100%. The description adds no parameter info, but with no parameters, the baseline is 4. No further documentation needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a 'canonical list of image-generation styles or presets'. It specifies the resource (styles) and action (return list). Given siblings are get_pricing and get_official_links, this tool is distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. Implied usage: if you need styles, use this. Siblings have different purposes, but no exclusions or context provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 3 tool updatesv0.1.0
    • First observedget_official_links
    • First observedget_pricing
    • First observedlist_styles
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TDQS

A3.6/5.0
Disambiguation5/5

Each tool targets a distinct resource: styles, pricing, or official links. There is no ambiguity between them.

Naming Consistency4/5

Tools use a verb_noun pattern, but mix 'list_' and 'get_' verbs. While both are clear, consistency would be improved by using a single verb.

Tool Count3/5

With only 3 tools, the server seems under-scoped for an image generation platform, but it may be intentionally focused on reference information.

Completeness2/5

The server lacks any tools for actual image generation, user management, or creation workflows, which are core to its stated domain.

Resources

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