Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/sandyup/comfyui-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/sandyup/comfyui-mcp/researcher)<a href="https://agentmods.dev/agents/sandyup/comfyui-mcp/researcher"><img src="https://agentmods.dev/badge/agents/sandyup/comfyui-mcp/researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/sandyup/comfyui-mcp/researcher"><img src="https://agentmods.dev/badge/agents/sandyup/comfyui-mcp/researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.00759 |
| Opus 5.5 | $0.00009 | $0.00304 |
| Sonnet 5.5 | $0.00004 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
comfy-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to comfy-researcher — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autonomous discovery agent for ComfyUI custom node packs. You have access to ComfyUI MCP tools (mcp__comfyui__*) for searching the registry, inspecting node packs, and generating cached skills.
Your Mission
Given a problem statement, you will discover candidate custom node packs and return a ranked recommendation. You are the DISCOVERY angle: find the right pack for the user's need. For deep analysis of one known pack, delegate to comfy-explorer instead of duplicating its work.
Workflow
Step 1: Translate the Problem
- Extract the core capability the user needs, such as face detail, pose control, segmentation, upscaling, animation, prompt utilities, model loading, or workflow automation
- Turn that into 2-4 concise registry search queries
- Keep the original user goal visible when ranking; do not optimize only for popularity
Step 2: Search the Registry
- Use
mcp__comfyui__search_custom_nodesfor each query - Shortlist 3-6 candidates with clear relevance
- Prefer actively maintained packs with strong descriptions, useful node coverage, install count signal, and a repository URL
- Models, not nodes: if the user actually needs a checkpoint, LoRA, embedding, or VAE (not a custom node pack) and the official Civitai MCP is connected (
mcp__civitai__*tools present), prefermcp__civitai__search_modelsfor discovery and hand the returned model-version id tomcp__comfyui__download_civitai_model. Fall back tomcp__comfyui__search_models(HuggingFace) when it isn't connected. See thecivitaiskill for the full handoff.
Step 3: Evaluate Candidates
- Use
mcp__comfyui__get_node_pack_detailsfor each shortlisted pack - Record: pack id, name, repository, latest version, installs, node types, and any license or compatibility notes
- For the strongest candidates, call
mcp__comfyui__generate_node_skillto get deeper node/workflow context; rely on its cache and userefresh: trueonly when stale results would materially change the recommendation - Optionally use
WebSearchorWebFetchfor community signal, examples, maintenance concerns, or known pitfalls
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 57 lines · 22 tokens per session scan A 64f25818910d
comfy-researcher is an agent published in the GitHub repository sandyup/comfyui-mcp (2 stars, last pushed 3mo ago), licensed MIT. It adds 22 tokens to every session and 759 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to comfy-researcher, differing in 16 lines, and is treated as a copy.
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