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MeiGen AI Design MCP Server

MCP server and CLI for AI image and video generation with gallery search, prompt enhancement, model listing, local preferences, ComfyUI workflows, MeiGen Cloud, and OpenAI-compatible provider support.

by MeiGen · submitted by oktofeesh1·added 2026-06-06·
Review first review before installing

Open the source and read safety notes before installing.

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Source URLs
https://raw.githubusercontent.com/jau123/MeiGen-AI-Design-MCP/main/README.md, https://github.com/jau123/MeiGen-AI-Design-MCP
Brand
MeiGen AI Design MCP
Brand domain
meigen.ai
Brand asset source
brandfetch
Safety notes
MeiGen can submit image and video generation jobs to external providers or a local ComfyUI backend., Image and video generation may spend credits, use paid APIs, or consume local GPU resources depending on the configured provider., Local reference images can be compressed and uploaded through the configured upload gateway before being sent to API providers., Video generation can take minutes, may time out at the MCP client, and should not be retried blindly because jobs or credits may already be in progress., ComfyUI workflow import and modification can run local workflows; review workflow JSON and custom nodes before use.
Privacy notes
API tokens, OpenAI-compatible credentials, provider base URLs, upload gateway URLs, ComfyUI URLs, preferences, recent generations, prompts, model IDs, and output paths can reveal private creative workflows., Uploaded reference images may become public URLs through the configured upload gateway before generation., Prompts, reference images, generated image URLs, generated video URLs, saved outputs, and favorite prompts can contain client work, brand plans, product images, personal likenesses, or unreleased campaigns., Keep secrets in MCP client environment configuration, review generated media before sharing, and remove local outputs when retention is no longer needed.
Author
MeiGen
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-06

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

63

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Needs review

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  • Source link availableRequired

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    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    No reviewed flag detected in metadata.

    Pending

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

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  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

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    Pending
  • Checksum metadata

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    Pending

Compare-driven decision checks

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  • Diverging trust signals identified

    No major trust-signal divergence found.

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Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

15 minutes

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    No review metadata found; increase manual validation.

    Pending
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done
  • Review privacy notesRequired

    Privacy notes are present.

    Done
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Missing

Review metadata is missing.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is missing.

Pending

verify

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Safety notes are available.

Done

verify

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Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

5 prerequisites to line up before setup. Have accounts and credentials ready first. Includes a review or approval gate.

0/5 ready
Account & credentials1Install & runtime2Review & approval215 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 4 privacy notes across 5 risk areas. Review closely: credentials & tokens, network access, third-party handling.

5 areas
  • SafetyThird-party handlingMeiGen can submit image and video generation jobs to external providers or a local ComfyUI backend.
  • SafetyThird-party handlingImage and video generation may spend credits, use paid APIs, or consume local GPU resources depending on the configured provider.
  • SafetyNetwork accessLocal reference images can be compressed and uploaded through the configured upload gateway before being sent to API providers.
  • SafetyGeneralVideo generation can take minutes, may time out at the MCP client, and should not be retried blindly because jobs or credits may already be in progress.
  • SafetyExecution & processesComfyUI workflow import and modification can run local workflows; review workflow JSON and custom nodes before use.
  • PrivacyCredentials & tokensAPI tokens, OpenAI-compatible credentials, provider base URLs, upload gateway URLs, ComfyUI URLs, preferences, recent generations, prompts, model IDs, and output paths can reveal private creative workflows.
  • PrivacyNetwork accessUploaded reference images may become public URLs through the configured upload gateway before generation.
  • PrivacyGeneralPrompts, reference images, generated image URLs, generated video URLs, saved outputs, and favorite prompts can contain client work, brand plans, product images, personal likenesses, or unreleased campaigns.
  • PrivacyCredentials & tokensKeep secrets in MCP client environment configuration, review generated media before sharing, and remove local outputs when retention is no longer needed.

Disclosure: MIT-licensed open-source MCP server and CLI. Some generation paths use paid or credit-based external services, while free tools and local ComfyUI workflows can be used without a MeiGen API token.

Safety notes

  • MeiGen can submit image and video generation jobs to external providers or a local ComfyUI backend.
  • Image and video generation may spend credits, use paid APIs, or consume local GPU resources depending on the configured provider.
  • Local reference images can be compressed and uploaded through the configured upload gateway before being sent to API providers.
  • Video generation can take minutes, may time out at the MCP client, and should not be retried blindly because jobs or credits may already be in progress.
  • ComfyUI workflow import and modification can run local workflows; review workflow JSON and custom nodes before use.

Privacy notes

  • API tokens, OpenAI-compatible credentials, provider base URLs, upload gateway URLs, ComfyUI URLs, preferences, recent generations, prompts, model IDs, and output paths can reveal private creative workflows.
  • Uploaded reference images may become public URLs through the configured upload gateway before generation.
  • Prompts, reference images, generated image URLs, generated video URLs, saved outputs, and favorite prompts can contain client work, brand plans, product images, personal likenesses, or unreleased campaigns.
  • Keep secrets in MCP client environment configuration, review generated media before sharing, and remove local outputs when retention is no longer needed.

Prerequisites

  • Node.js 18 or newer.
  • MCP client that can launch a local Node stdio server.
  • Optional MeiGen API token, OpenAI-compatible API key, or local ComfyUI workflow configuration for generation tools.
  • Provider pricing, credits, model limits, and content policy reviewed before image or video generation.
  • Local reference images, prompts, and generated outputs reviewed for rights, consent, and privacy.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
15 minutes
Difficulty
advanced
Tool listing metadata
Disclosure
MIT-licensed open-source MCP server and CLI. Some generation paths use paid or credit-based external services, while free tools and local ComfyUI workflows can be used without a MeiGen API token.
Full copyable content
{
  "mcpServers": {
    "meigen": {
      "command": "npx",
      "args": ["-y", "meigen"],
      "env": {
        "MEIGEN_API_TOKEN": "{meigen-api-token}"
      }
    }
  }
}

About this resource

Content

MeiGen AI Design MCP Server is a Node-based MCP server and CLI for creative image and video workflows. It exposes tools for searching an inspiration gallery, retrieving prompt examples, enhancing prompts, listing models, generating images, generating videos, managing ComfyUI workflows, and storing local preferences.

Use it when Claude needs a dedicated design-generation interface rather than a generic image prompt. MeiGen can route generation through MeiGen Cloud, OpenAI-compatible image APIs, or local ComfyUI workflows, so provider setup and cost review matter before calling generation tools.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, README, npm metadata, license, package metadata, server registration, config loader, image/video generation tools, and upload helper for current behavior.

Features

  • Run as an npm stdio MCP server with npx -y meigen.
  • Search a curated prompt and inspiration gallery.
  • Retrieve prompt examples and associated image metadata.
  • Enhance short creative ideas into richer image prompts.
  • List available image and video models across configured providers.
  • Generate images through MeiGen Cloud, OpenAI-compatible APIs, or local ComfyUI workflows.
  • Generate videos through the MeiGen provider with model, duration, resolution, aspect-ratio, first-frame, last-frame, and reference-video options.
  • Compress and upload local reference images for API providers.
  • Manage user preferences, preferred styles, favorite prompts, and recent generations.
  • Import, view, modify, delete, and use ComfyUI workflow templates.
  • Use the same package as a standalone CLI for scripted generation.

Installation

Add the server to an MCP client with npm:

{
  "mcpServers": {
    "meigen": {
      "command": "npx",
      "args": ["-y", "meigen"],
      "env": {
        "MEIGEN_API_TOKEN": "{meigen-api-token}"
      }
    }
  }
}

The inspiration, prompt-enhancement, model-listing, workflow, and preference tools can be useful before generation credentials are configured. For image or video generation, configure one of the provider paths supported by upstream: MeiGen API token, OpenAI-compatible API credentials, or local ComfyUI workflows.

Use Cases

  • Search a prompt gallery for visual direction before drafting a campaign image.
  • Expand a terse product, logo, poster, or social-media idea into a stronger prompt.
  • Generate a small set of reviewed image directions through a configured provider.
  • Generate a short video only after confirming model, duration, resolution, and expected cost.
  • Use local ComfyUI workflows from Claude while keeping workflow files under review.
  • Save preferred visual style, aspect ratio, model, and favorite prompts for repeated design sessions.
  • Use the package as a CLI in controlled scripts after reviewing secrets and output paths.

Safety and Privacy

Treat MeiGen as a generation and upload bridge. Local reference images may be compressed and uploaded to a public URL before API-provider generation, while ComfyUI workflows can run locally and may depend on local models, custom nodes, or GPU resources. Review source images, prompts, workflow JSON, and model choices before approving generation.

Generated image and video calls can spend credits or hit paid APIs. The server source instructs clients not to parallelize videos and warns that timed-out video jobs may still be running. Confirm expensive, slow, multi-image, video, high-resolution, or reference-video calls before use, and review rights, likeness, brand, platform, and client confidentiality obligations before sharing outputs.

Duplicate Check

No jau123/MeiGen-AI-Design-MCP, MeiGen AI Design MCP Server, meigen package entry, or matching source URL entry was found in content/mcp or README.md.

Source citations

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How it compares

MeiGen AI Design MCP Server side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field

MCP server and CLI for AI image and video generation with gallery search, prompt enhancement, model listing, local preferences, ComfyUI workflows, MeiGen Cloud, and OpenAI-compatible provider support.

Open dossier

MCP and REST server for creating short-form videos from scene text, Pexels search terms, text-to-speech, captions, background music, Whisper captions, FFmpeg, and Remotion rendering.

Open dossier

MCP server for controlling DaVinci Resolve Studio through the official scripting API, with tools for projects, timelines, media pools, render setup, review markers, grading, Fusion, Fairlight, and source-safe media analysis.

Open dossier

Official Agentset MCP server that lets Claude retrieve cited knowledge-base results from an Agentset namespace through the `knowledge-base-retrieve` tool, with optional tenant scoping and custom tool descriptions.

Open dossier
Next steps
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
Submitteroktofeesh1oktofeesh1oktofeesh1oktofeesh1
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandMeiGen AI Design MCP logoMeiGen AI Design MCPDaVinci Resolve MCP Server logoDaVinci Resolve MCP ServerAgentset logoAgentset
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
AuthorMeiGenDavid GyoriSamuel GurskyAgentset
Added2026-06-062026-06-062026-06-062026-06-06
Platforms
Harness
Source repo
Safety notesMeiGen can submit image and video generation jobs to external providers or a local ComfyUI backend. Image and video generation may spend credits, use paid APIs, or consume local GPU resources depending on the configured provider. Local reference images can be compressed and uploaded through the configured upload gateway before being sent to API providers. Video generation can take minutes, may time out at the MCP client, and should not be retried blindly because jobs or credits may already be in progress. ComfyUI workflow import and modification can run local workflows; review workflow JSON and custom nodes before use.Short Video Maker runs an HTTP server with MCP SSE routes and REST routes for creating and serving generated videos. The create-short-video tool queues video rendering work that can consume CPU, memory, disk, browser rendering resources, and optional GPU resources. Generated videos combine user-provided narration text, Pexels search terms, downloaded background clips, local music assets, TTS output, captions, and rendered media. The server stores generated videos and temporary files under its configured data directory. Validate scene text, search terms, claims, branding, and rights before publishing generated videos to TikTok, Instagram, YouTube, or other platforms.DaVinci Resolve MCP Server can launch or reconnect to Resolve, switch pages, create or open projects, modify timelines, manage media pools, write markers, change render settings, and queue jobs. Extension-authoring tools can install or remove Resolve scripts, Fuses, DCTLs, ACES DCTLs, presets, and page scripts. Source media is intended to remain immutable by default, but operators must still review requests that relink, replace, transcode, proxy, render, export, or create media derivatives. The default server is local stdio, but the local control panel starts a single-user browser server; keep it on trusted local interfaces only. Require confirmation before deleting projects, replacing clips, changing project settings, installing extensions, updating metadata, or queuing renders. Keep Resolve external scripting set to `Local` unless you have a separate remote-control security plan.The MCP server sends Claude's retrieval queries to the Agentset API using the configured API key and namespace. The `knowledge-base-retrieve` tool can return up to 100 results per call and can rerank results by relevance. Namespace and tenant selection control which indexed documents are searchable; review them before connecting a shared agent. API keys should be scoped, rotated, and stored only in the MCP server environment or a secret manager. Custom tool descriptions can influence when the model calls the retrieval tool, so review them before use in production workflows.
Privacy notesAPI tokens, OpenAI-compatible credentials, provider base URLs, upload gateway URLs, ComfyUI URLs, preferences, recent generations, prompts, model IDs, and output paths can reveal private creative workflows. Uploaded reference images may become public URLs through the configured upload gateway before generation. Prompts, reference images, generated image URLs, generated video URLs, saved outputs, and favorite prompts can contain client work, brand plans, product images, personal likenesses, or unreleased campaigns. Keep secrets in MCP client environment configuration, review generated media before sharing, and remove local outputs when retention is no longer needed.`PEXELS_API_KEY` is sent to the Pexels API when searching for background videos. Scene text, search terms, generated narration, captions, video IDs, logs, output filenames, and render status can reveal campaign ideas, private scripts, brand plans, or client work. Generated files remain on disk until removed according to the deployment's data-directory and retention practices. Pexels requests, model downloads, Docker pulls, npm installs, and platform uploads may expose network metadata to third parties outside the MCP client.Project names, timelines, clip names, media paths, markers, metadata, render paths, transcripts, thumbnails, analysis artifacts, logs, and Resolve scripting paths can be exposed to the MCP client. Media analysis can produce sidecar files, scratch artifacts, frame paths, transcripts, searchable indexes, and reports that may include private footage details. Host-chat visual analysis can expose selected frame images to the active MCP client or vision-capable model provider. Local logs and analysis reports may contain absolute media paths, project names, clip metadata, speaker text, visual descriptions, and render settings. Store generated analysis artifacts and exports inside approved project or scratch directories and delete them when no longer needed.Retrieved chunks can include private documents, product specs, policies, support content, internal procedures, historical project information, or customer-specific data. Retrieval queries, namespace IDs, tenant IDs, document chunks, citations, and tool outputs may be visible to the MCP client, model provider, Agentset logs, and application telemetry. Tenant IDs are useful for data segregation, but incorrect tenant or namespace configuration can expose the wrong knowledge base. Do not paste API keys, namespace IDs, tenant IDs, or retrieved private chunks into shared issue reports, screenshots, or repository files.
Prerequisites
  • Node.js 18 or newer.
  • MCP client that can launch a local Node stdio server.
  • Optional MeiGen API token, OpenAI-compatible API key, or local ComfyUI workflow configuration for generation tools.
  • Provider pricing, credits, model limits, and content policy reviewed before image or video generation.
  • Node.js or Docker available on the machine that will run the video server.
  • Pexels API key configured through `PEXELS_API_KEY`.
  • Enough CPU, memory, and disk for Whisper, Kokoro, FFmpeg, Remotion, temporary files, and rendered videos.
  • MCP client that can connect to an SSE MCP endpoint.
  • DaVinci Resolve Studio 18.5 or newer; the free edition does not support the required external scripting API.
  • Resolve external scripting set to `Local`.
  • Python 3.10 or newer, with Python 3.10-3.12 recommended for the broadest Resolve compatibility.
  • A local MCP client that can launch stdio servers under the same user account that operates Resolve.
  • Agentset account or self-hosted Agentset deployment with a populated namespace.
  • Agentset API key with access to the namespace Claude should query.
  • Node.js 18.17 or newer for running the `@agentset/mcp` package.
  • Namespace ID selected with `--ns` or `AGENTSET_NAMESPACE_ID`.
Install
Run `npx -y meigen` from an MCP client, or use the upstream plugin/init commands after reviewing provider credentials and generated-media costs.
Run the upstream Docker image or `npx short-video-maker` with `PEXELS_API_KEY` set, then connect an MCP client to the server's `/mcp/sse` endpoint.
npx davinci-resolve-mcp setup
Run `npx @agentset/mcp --ns <namespace-id>` with `AGENTSET_API_KEY` set in the MCP server environment.
Config
{
  "mcpServers": {
    "meigen": {
      "command": "npx",
      "args": ["-y", "meigen"],
      "env": {
        "MEIGEN_API_TOKEN": "{meigen-api-token}"
      }
    }
  }
}
{
  "mcpServers": {
    "short-video-maker": {
      "url": "{short-video-maker-sse-url}"
    }
  }
}
{
  "mcpServers": {
    "davinci-resolve": {
      "command": "npx",
      "args": [
        "davinci-resolve-mcp",
        "server"
      ],
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "agentset": {
      "command": "npx",
      "args": ["-y", "@agentset/mcp@latest", "--ns", "ns_xxx"],
      "env": {
        "AGENTSET_API_KEY": "agentset_xxx"
      }
    }
  }
}
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