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ComfyUI MCP Server

Source-install MCP server for controlling a local ComfyUI instance so Claude can generate, view, regenerate, manage, and publish image, audio, and video assets through workflow-backed tools.

by Joe Norton · 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://github.com/joenorton/comfyui-mcp-server/blob/main/README.md, https://github.com/joenorton/comfyui-mcp-server
Brand
ComfyUI MCP Server
Brand domain
github.com
Safety notes
ComfyUI MCP Server can submit prompts and workflows to a local ComfyUI instance, create generated media, poll jobs, cancel jobs, and publish assets into project directories., Generated images, audio, and video can contain unsafe, infringing, biased, misleading, or policy-sensitive content depending on prompts, models, LoRAs, and workflows., Publishing tools can copy, compress, convert, overwrite, and update manifest entries for assets, so verify target filenames and directories before use., Custom workflows can expose arbitrary parameters and may run heavy GPU workloads or fail if nodes, models, or paths are missing., Keep the server bound to local trusted clients unless you have added appropriate authentication and network controls.
Privacy notes
Prompts, negative prompts, generated media, workflow parameters, model names, job IDs, asset metadata, and publish paths can appear in MCP responses, logs, and model transcripts., Generated assets may be stored in ComfyUI output folders, the MCP asset registry, project publish directories, or manifests., Do not feed private images, brand assets, customer materials, or regulated media into workflows unless the local model environment is approved for that data., Review model and workflow licenses before publishing or redistributing generated assets.
Author
Joe Norton
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

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    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

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

30 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

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

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

4 prerequisites to line up before setup. Includes a review or approval gate.

0/4 ready
Install & runtime3Review & approval130 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 4 privacy notes across 3 risk areas. Review closely: network access.

3 areas
  • SafetyGeneralComfyUI MCP Server can submit prompts and workflows to a local ComfyUI instance, create generated media, poll jobs, cancel jobs, and publish assets into project directories.
  • SafetyGeneralGenerated images, audio, and video can contain unsafe, infringing, biased, misleading, or policy-sensitive content depending on prompts, models, LoRAs, and workflows.
  • SafetyLocal filesPublishing tools can copy, compress, convert, overwrite, and update manifest entries for assets, so verify target filenames and directories before use.
  • SafetyLocal filesCustom workflows can expose arbitrary parameters and may run heavy GPU workloads or fail if nodes, models, or paths are missing.
  • SafetyNetwork accessKeep the server bound to local trusted clients unless you have added appropriate authentication and network controls.
  • PrivacyLocal filesPrompts, negative prompts, generated media, workflow parameters, model names, job IDs, asset metadata, and publish paths can appear in MCP responses, logs, and model transcripts.
  • PrivacyLocal filesGenerated assets may be stored in ComfyUI output folders, the MCP asset registry, project publish directories, or manifests.
  • PrivacyGeneralDo not feed private images, brand assets, customer materials, or regulated media into workflows unless the local model environment is approved for that data.
  • PrivacyGeneralReview model and workflow licenses before publishing or redistributing generated assets.

Safety notes

  • ComfyUI MCP Server can submit prompts and workflows to a local ComfyUI instance, create generated media, poll jobs, cancel jobs, and publish assets into project directories.
  • Generated images, audio, and video can contain unsafe, infringing, biased, misleading, or policy-sensitive content depending on prompts, models, LoRAs, and workflows.
  • Publishing tools can copy, compress, convert, overwrite, and update manifest entries for assets, so verify target filenames and directories before use.
  • Custom workflows can expose arbitrary parameters and may run heavy GPU workloads or fail if nodes, models, or paths are missing.
  • Keep the server bound to local trusted clients unless you have added appropriate authentication and network controls.

Privacy notes

  • Prompts, negative prompts, generated media, workflow parameters, model names, job IDs, asset metadata, and publish paths can appear in MCP responses, logs, and model transcripts.
  • Generated assets may be stored in ComfyUI output folders, the MCP asset registry, project publish directories, or manifests.
  • Do not feed private images, brand assets, customer materials, or regulated media into workflows unless the local model environment is approved for that data.
  • Review model and workflow licenses before publishing or redistributing generated assets.

Prerequisites

  • A local ComfyUI installation with required models and workflows.
  • Python and the repository requirements installed from the source checkout.
  • The MCP server launched from the cloned repository or with paths adjusted for your client.
  • Approved prompts, source assets, model licenses, and publish locations for generated media.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
30 minutes
Difficulty
advanced
Full copyable content
{
  "mcpServers": {
    "comfyui-mcp-server": {
      "command": "python",
      "args": ["server.py", "--stdio"],
      "env": {
        "COMFYUI_URL": "",
        "COMFY_MCP_WORKFLOW_DIR": ""
      }
    }
  }
}

About this resource

Content

ComfyUI MCP Server is a source-install Model Context Protocol server that lets Claude control a local ComfyUI instance. It exposes tools for generating media, viewing generated images, regenerating assets with parameter overrides, polling jobs, listing assets, inspecting metadata, configuring defaults, running custom workflows, and publishing approved assets into project directories.

The project is aimed at local iterative media workflows. It can be useful for design exploration, web assets, prompt iteration, and custom ComfyUI workflow automation, but generated media still needs human review before it is shipped, published, or reused.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, README, Python requirements, server implementation, ComfyUI client, generation tool, publish tool, and license file for current setup, transport options, tool behavior, asset handling, and licensing.

Features

  • Source-install Python MCP server for local ComfyUI.
  • Stdio mode available from server.py --stdio; upstream also documents local streamable HTTP usage.
  • Workflow-backed generation tools such as generate_image, generate_song, regenerate, and custom workflow tools discovered from workflow JSON files.
  • Asset tools for viewing images, listing recent assets, and reading metadata.
  • Job tools for queue status, job polling, and cancellation.
  • Configuration tools for defaults and model listing.
  • Publish tools for copying, optimizing, and manifesting approved generated assets.
  • Apache-2.0 license.

Installation

Clone the repository, install dependencies, start ComfyUI locally, and configure the MCP server from the source checkout:

git clone https://github.com/joenorton/comfyui-mcp-server
cd comfyui-mcp-server
pip install -r requirements.txt
{
  "mcpServers": {
    "comfyui-mcp-server": {
      "command": "python",
      "args": ["server.py", "--stdio"],
      "env": {
        "COMFYUI_URL": "",
        "COMFY_MCP_WORKFLOW_DIR": ""
      }
    }
  }
}

After restarting the MCP client, ask Claude to generate an approved asset, inspect the result, and iterate only after reviewing the output.

Use Cases

  • Generate image concepts from approved prompts.
  • Iterate on a generated asset without restating all parameters.
  • Run custom ComfyUI workflows exposed as MCP tools.
  • Ask Claude to list available models and defaults before generation.
  • Poll or cancel long-running ComfyUI jobs.
  • View generated image assets inside the client workflow.
  • Publish reviewed assets into a web project directory with controlled filenames.

Safety and Privacy

ComfyUI MCP Server can create and publish generated media. Review prompts, models, workflow licenses, source inputs, and output rights before using assets in public or commercial contexts. Generated media can include unsafe, misleading, copyrighted, trademarked, biased, or otherwise sensitive content, even when prompts look harmless.

The server can store generated assets, metadata, workflow history, job IDs, publish paths, and manifest updates. Keep it connected only to trusted local clients, review publish targets before writing, and avoid sending private images, brand assets, customer materials, or regulated media through workflows unless your environment is approved for that data.

Duplicate Check

Existing MCP content includes image, browser, and design-related integrations, but no dedicated entry for joenorton/comfyui-mcp-server was found in content/mcp. This entry is distinct because it covers a local ComfyUI MCP bridge for generated media workflows, job management, asset inspection, custom workflow execution, and publish tools.

Source citations

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How it compares

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

3 trust signals differ across this comparison (Review status, Source provenance, Submitter).

Field

Source-install MCP server for controlling a local ComfyUI instance so Claude can generate, view, regenerate, manage, and publish image, audio, and video assets through workflow-backed tools.

Open dossier

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

Memesio MCP Server is a hosted MCP endpoint for meme template discovery, captioned meme creation, share links, and AI-assisted meme generation. Public tools support anonymous/rate-limited usage, while optional developer or agent keys unlock higher-rate, premium, and AI-powered actions.

Open dossier

Official MiniMax MCP server for using MiniMax text-to-speech, voice cloning, voice design, image generation, video generation, music generation, and media retrieval APIs from Claude and other MCP clients.

Open dossier
Next steps
Trust
Review statusDiffersNot reviewedNot reviewedReviewedJSONbored · 2026-05-10Not reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceDiffersSource-backedSource-backedSubmission linkedSource submissionSource-backed
SubmitterDiffersoktofeesh1oktofeesh1vy35oktofeesh1
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandMeiGen AI Design MCP logoMeiGen AI Design MCPMemesio logoMemesioMiniMax logoMiniMax
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
AuthorJoe NortonMeiGenMemesioMiniMax-AI
Added2026-06-062026-06-062026-05-082026-06-06
Platforms
Harness
Source repo
Safety notesComfyUI MCP Server can submit prompts and workflows to a local ComfyUI instance, create generated media, poll jobs, cancel jobs, and publish assets into project directories. Generated images, audio, and video can contain unsafe, infringing, biased, misleading, or policy-sensitive content depending on prompts, models, LoRAs, and workflows. Publishing tools can copy, compress, convert, overwrite, and update manifest entries for assets, so verify target filenames and directories before use. Custom workflows can expose arbitrary parameters and may run heavy GPU workloads or fail if nodes, models, or paths are missing. Keep the server bound to local trusted clients unless you have added appropriate authentication and network controls.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.Review generated memes and share links before publishing, and avoid uploading sensitive images or private text.Most generation tools call MiniMax APIs and can incur account costs; only enable them for users who are authorized to spend from the MiniMax account. Voice cloning and voice design can create synthetic voices; obtain consent and rights for any source audio or identity-like voice prompt before use. Image-to-video, voice cloning, audio playback, and local output modes can read local files or URLs and send media to MiniMax APIs. Generated image, audio, video, and music outputs should be reviewed for policy, copyright, likeness, brand, and release constraints before publication. The API key and API host must match the selected region or requests can fail with authentication errors.
Privacy notesPrompts, negative prompts, generated media, workflow parameters, model names, job IDs, asset metadata, and publish paths can appear in MCP responses, logs, and model transcripts. Generated assets may be stored in ComfyUI output folders, the MCP asset registry, project publish directories, or manifests. Do not feed private images, brand assets, customer materials, or regulated media into workflows unless the local model environment is approved for that data. Review model and workflow licenses before publishing or redistributing generated assets.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.Prompts, source images, captions, API keys, generated outputs, and shared asset URLs may be sent through the integration.Prompts, preview text, lyrics, source audio, first-frame images, uploaded files, generated media requests, and task IDs may be sent to MiniMax APIs and included in MCP client or model logs. MINIMAX_API_KEY must stay in environment variables or secret managers and should never be committed to MCP config files. Local output mode can write generated files under the configured base path, and returned file paths may reveal workstation directory structure to the MCP client. URL resource mode returns generated media URLs that may need access controls, retention review, and sharing policy before being pasted into chats or tickets.
Prerequisites
  • A local ComfyUI installation with required models and workflows.
  • Python and the repository requirements installed from the source checkout.
  • The MCP server launched from the cloned repository or with paths adjusted for your client.
  • Approved prompts, source assets, model licenses, and publish locations for generated media.
  • 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.
— none listed
  • MiniMax API key from the correct regional MiniMax platform.
  • MINIMAX_API_HOST set to the matching Global or Mainland endpoint for the API key.
  • uv or uvx available to run the Python package.
  • Optional MINIMAX_MCP_BASE_PATH when using local output mode for generated media files.
Install
git clone https://github.com/joenorton/comfyui-mcp-server && cd comfyui-mcp-server && pip install -r requirements.txt
Run `npx -y meigen` from an MCP client, or use the upstream plugin/init commands after reviewing provider credentials and generated-media costs.
claude mcp add --transport http memesio https://memesio.com/api/mcp
uvx minimax-mcp
Config
{
  "mcpServers": {
    "comfyui-mcp-server": {
      "command": "python",
      "args": ["server.py", "--stdio"],
      "env": {
        "COMFYUI_URL": "",
        "COMFY_MCP_WORKFLOW_DIR": "",
        "COMFYUI_OUTPUT_ROOT": "",
        "COMFY_MCP_ASSET_TTL_HOURS": "24"
      }
    }
  }
}
{
  "mcpServers": {
    "meigen": {
      "command": "npx",
      "args": ["-y", "meigen"],
      "env": {
        "MEIGEN_API_TOKEN": "{meigen-api-token}"
      }
    }
  }
}
{
  "mcpServers": {
    "memesio": {
      "type": "http",
      "url": "https://memesio.com/api/mcp"
    }
  }
}
{
  "mcpServers": {
    "minimax": {
      "command": "uvx",
      "args": [
        "minimax-mcp"
      ],
      "env": {
        "MINIMAX_API_KEY": "insert-your-api-key-here",
        "MINIMAX_API_HOST": "https://api.minimax.io",
        "MINIMAX_API_RESOURCE_MODE": "url"
      },
      "type": "stdio"
    }
  }
}
Citations
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