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/Lucas-Servi/kegg-mcp-server-pythonWrote 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/commands/lucas-servi/kegg-mcp-server-python/kegg-drug)<a href="https://agentmods.dev/commands/lucas-servi/kegg-mcp-server-python/kegg-drug"><img src="https://agentmods.dev/badge/commands/lucas-servi/kegg-mcp-server-python/kegg-drug/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/commands/lucas-servi/kegg-mcp-server-python/kegg-drug"><img src="https://agentmods.dev/badge/commands/lucas-servi/kegg-mcp-server-python/kegg-drug.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 | $0.00013 | $0.00224 |
| Opus 5 | $0.00006 | $0.00112 |
| Sonnet 5 | $0.00003 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
kegg-drug scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Drug Investigation
Investigate a drug's mechanism of action, targets, and interactions.
- Call
search_drugswith:$ARGUMENTS - Call
get_drug_infofor the top match to retrieve targets, classification, and metabolism. - For each target gene listed, call
search_genesin human (hsa) to get the KEGG gene ID. - Call
find_related_entriesto identify pathways each target participates in. - Call
get_drug_interactionsto screen for drug-drug interactions. - Present a structured report:
- Drug name, formula, and classification
- Mechanism of action (from target + pathway data)
- Target genes and their biological roles
- Key pathways affected
- Drug-drug interactions (if any)
- Suggested follow-ups: "Try
/kegg-pathwayto explore a target pathway in detail."
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.
- 9d ago First seen · 23 lines · 13 tokens per session scan A 5759fa6094f3
kegg-drug is a command published in the GitHub repository Lucas-Servi/kegg-mcp-server-python (3 stars, last pushed 26d ago), licensed MIT. It adds 13 tokens to every session and 224 once invoked, about $0.0001 per session on Opus 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.
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