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AlphaGenome MCP Server

by taehojo
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TypeScript
Remote

atlas_lookup_variants

Look up precomputed AlphaGenome scores for up to 500 single-nucleotide variants in one call and rank them by impact; unsupported or rejected variants are listed separately with reasons.

Instructions

Look up precomputed AlphaGenome scores for up to 500 single-nucleotide variants in one call and rank them.

Returns one row per variant (its strongest score and where it was seen), ranked. Default scorer: AVI_SCORE (AlphaGenome Variant Impact), one number per variant. With several scorers the ranking uses the largest absolute quantile. Variants the Atlas does not hold and variants it rejects (for example a reference base that does not match hg38) are listed separately with the reason; they do not fail the call.

The Atlas holds precomputed AlphaGenome scores for single-nucleotide substitutions on the human reference genome (hg38, chr1-22, chrX, chrY). Indels and multi-nucleotide variants are not in it; use predict_variant_effect for those.

The response is a summary, never a full score matrix: ranked rows only, capped at top_n (default 25, max 100) and at 40,000 characters.

Results are AlphaGenome model predictions for research prioritization, not clinical classifications: scores and calibrated quantiles are reported as returned, and no pathogenic/benign call is made.

Example: "Rank these 200 GWAS SNPs by their Atlas scores"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoRows to return (default: 25, max: 100)
scorersNoOptional: scorer names to use instead of the defaults. Names come from atlas_list_scorers and are the same for both sources, except the AVI scorers, which the Atlas alone serves.
variantsYesSingle-nucleotide variants to look up (1-500)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so richly: one row per variant, default AVI_SCORE, largest-absolute-quantile ranking with multiple scorers, missing/rejected variants listed separately with reasons rather than failing the call, the 40,000-character response cap, and a research-only (non-clinical) disclaimer. This is well beyond what the schema conveys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and result shape, then scope limits, then caveats; each paragraph is purposeful. Slightly long, with the closing example and dual disclaimers bordering on extras, but nothing misleading or padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must explain returns, and it does: ranked rows only, capped at top_n and 40,000 characters, with out-of-Atlas/rejected variants reported separately. An agent has everything needed to call and interpret it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds real meaning: top_n defaults to 25 and caps at 100, and the choice of scorers changes the ranking method (largest absolute quantile). The only gap is that scoring syntax/format details remain in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (look up precomputed scores), resource (AlphaGenome SNV scores), and scope (up to 500 in one call, ranked). It distinguishes itself from siblings by noting indels/MNVs are out of scope and belong to predict_variant_effect, and the singular sibling atlas_lookup_variant is implicitly contrasted by the batch framing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names the alternative explicitly for the out-of-scope case ('Indels and multi-nucleotide variants are not in it; use predict_variant_effect for those') and points to atlas_list_scorers as the source of valid scorer names. Both when-to-use and when-not-to-use are covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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