everycure-kg

everycure-kg is a skill for Claude Code from pascalwhoop/medical-mcps. It costs 152 tokens per session (5,198 once invoked), scanned A, original, MIT.

A guide to Everycure’s biomedical knowledge graph, a connected database of drugs, diseases, genes, proteins, and biological pathways.

In plain words
What is it for?
Finding possible drug repurposing links, exploring biological mechanisms, and researching connections between medicines, diseases, genes, proteins, and pathways.
Why use it?
It helps avoid queries that grow too large or hit highly connected nodes in the graph. It also explains the graph’s structure and built-in query safety checks.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Part of the medical-mcps plugin — 2 skills, 2 MCP servers shipped together

Good fit Finding possible drug repurposing links, exploring biological mechanisms, and researching connections between medicines, diseases, genes, proteins, and pathways.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pascalwhoop/medical-mcps/everycure-kg
Install

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.

Any agent
npx skills add pascalwhoop/medical-mcps --skill everycure-kg
Clone the repo
git clone --depth 1 https://github.com/pascalwhoop/medical-mcps

Made for: Claude Code.

Or install medical-mcps, the plugin that ships this one along with the rest of its 2 skills, 2 MCP servers.

Wrote 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.

agentmods badge for everycure-kg

README.md
[![agentmods](https://agentmods.dev/badge/skills/pascalwhoop/medical-mcps/everycure-kg/github.svg)](https://agentmods.dev/skills/pascalwhoop/medical-mcps/everycure-kg)
Your own site
<a href="https://agentmods.dev/skills/pascalwhoop/medical-mcps/everycure-kg"><img src="https://agentmods.dev/badge/skills/pascalwhoop/medical-mcps/everycure-kg/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.

agentmods 80×15 button for everycure-kg

Your own site · 80×15
<a href="https://agentmods.dev/skills/pascalwhoop/medical-mcps/everycure-kg"><img src="https://agentmods.dev/badge/skills/pascalwhoop/medical-mcps/everycure-kg.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 152 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,198 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00152 $0.05198
Opus 5 $0.00076 $0.02599
Sonnet 5 $0.00030 $0.01040
Haiku 4.5 $0.00015 $0.00520

Measured 11d ago against content hash f45173fcf984, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

everycure-kg 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 11d 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.

.claude/skills/everycure-kg/SKILL.md · 600 lines

How it starts

The opening of the file, as written. The whole thing — 600 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Everycure Knowledge Graph Skill

Overview

The Everycure KG is a massive biomedical knowledge graph (9.2M nodes, 77M relationships) built on the Biolink Model. It integrates data on drugs, diseases, genes, proteins, pathways, and their relationships.

Key Challenge: The graph is extremely densely connected. Naive queries cause path explosion (~440x growth per hop).

Safety Built-In: The MCP server includes automatic safety checks:

  • Warns on high-degree nodes (>1K edges)
  • Blocks queries on super-hubs (>10K edges)
  • Prevents path explosion before executing queries
  • Handles schema quirks automatically in predefined metapaths

This skill teaches you to query effectively and work within the safety guardrails.


Quick Start

Finding Drug Repurposing Opportunities

Question: "Does Metformin treat Idiopathic Pulmonary Fibrosis?"

Step 1: Find node IDs

# Use execute_cypher to find nodes
result = execute_cypher("""
    MATCH (d) WHERE d.name CONTAINS 'Metformin' AND 'biolink:Drug' IN labels(d)
    RETURN d.id, d.name LIMIT 5
""")
# Result: CHEBI:6801

result = execute_cypher("""
    MATCH (dis) WHERE dis.name CONTAINS 'pulmonary fibrosis' AND 'biolink:Disease' IN labels(dis)
    RETURN dis.id, dis.name LIMIT 5
""")
# Result: MONDO:0800029

Step 2: Check direct treatment relationship (1-hop)

result = find_paths_by_metapath(
    source_id="CHEBI:6801",
    target_id="MONDO:0800029",
    metapath_name="drug_to_disease_direct"
)
# Result: FOUND - Direct treatment relationship exists!

Step 3: Find mechanistic targets (2-hop)

result = find_paths_by_metapath(
    source_id="CHEBI:6801",
    target_id="MONDO:0800029",
    metapath_name="drug_to_disease_via_target"
)
# Result: 50+ proteins including HDAC6 (AMPK pathway)

Core Principles

1. Always COUNT Before RETURN

Path explosion happens when you RETURN data before counting.

// WRONG (will hang on large results):
MATCH (d)-[r1]-(mid)-[r2]-(target)
WHERE d.id = $drug_id
RETURN d, mid, target LIMIT 100

// CORRECT (count first):
MATCH (d)-[r1]-(mid)-[r2]-(target)
WHERE d.id = $drug_id
RETURN COUNT(*) as path_count
// If path_count < 1000, then run:
// MATCH... RETURN d, mid, target LIMIT 100

Read the full file on GitHub · 600 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 11d ago First seen · 600 lines · 152 tokens per session scan A f45173fcf984

Subscribe to this mod's changes

everycure-kg is a skill published in the GitHub repository pascalwhoop/medical-mcps (23 stars, last pushed 9d ago), licensed MIT. It adds 152 tokens to every session and 5,198 once invoked, about $0.0008 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 2026-08-30.

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