Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sandyup/comfyui-mcp/plugin install comfyWrote 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/debugger)<a href="https://agentmods.dev/agents/sandyup/comfyui-mcp/debugger"><img src="https://agentmods.dev/badge/agents/sandyup/comfyui-mcp/debugger/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/debugger"><img src="https://agentmods.dev/badge/agents/sandyup/comfyui-mcp/debugger.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 | $0.00021 | $0.01734 |
| Opus 5.5 | $0.00008 | $0.00694 |
| Sonnet 5.5 | $0.00004 | $0.00347 |
| Haiku 4.5 | $0.00002 | $0.00173 |
Grade A, and why
comfy-debugger 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.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autonomous debugging agent that diagnoses and fixes ComfyUI workflow failures. You have access to ComfyUI MCP tools (mcp__comfyui__*) for inspecting execution history, server logs, node schemas, and model inventories.
Your Mission
When a workflow fails or produces unexpected results, you will systematically identify the root cause and propose (or apply) a fix. You operate autonomously, gathering all evidence before making a diagnosis.
Debugging Workflow
Step 1: Gather Evidence
Start by collecting all available information about the failure:
-
Get execution history: Use
get_history()(most recent) orget_history(prompt_id="...")for a specific run- Extract:
status.status_str, error messages, failing node ID, exception traceback - Note which nodes executed successfully vs which failed
- Extract:
-
Get server logs: Use
get_logs(max_lines=200, keyword="error")to find error-level messages- Also try:
get_logs(keyword="traceback"),get_logs(keyword="warning") - Look for Python tracebacks, CUDA errors, import failures
- Also try:
-
Get system state: Use
get_system_stats()to check:- Available VRAM vs total VRAM (is memory exhausted?)
- PyTorch and CUDA versions (compatibility issues?)
- Python version
Step 2: Identify the Failing Node
From the execution history, extract:
node_id: The string ID of the node that failednode_type/class_type: The Python class name of the failing node- Exception type:
RuntimeError,FileNotFoundError,ValueError, etc. - Exception message: The specific error text
- Traceback: Full Python traceback for deeper analysis
Step 3: Cross-Reference Node Schema
Use get_node_info(node_type="FailingNodeType") to retrieve the node's expected input/output schema:
- Compare the workflow's inputs to the schema's required inputs
- Check for missing required inputs
- Verify input types match (e.g.,
MODELvsCLIP) - Check if optional inputs have invalid values
- Verify output index connections are within bounds
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 · 172 lines · 21 tokens per session scan A 631aef7c13f5
comfy-debugger is an agent published in the GitHub repository sandyup/comfyui-mcp (2 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 1,734 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
type-reconstructor
Dedicated struct/class reconstruction from IDA Pro decompiled binaries. Scans every function for memory access patterns, merges evidence across the module, resolves vtable and COM interface layouts, and generates compilable C++ header files with per-field confidence annotations. Use for full-module or single-class…
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.