AlphaFold Sovereign MCP

by smaniches

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Python

Remote

Detect Intrinsically Disordered Regions

detect_intrinsically_disordered

Read-onlyIdempotent

Flag low-confidence modeled regions as intrinsic-disorder candidates.

Instructions

Flag low-confidence modeled regions as intrinsic-disorder candidates.

Reads per-residue AlphaFold pLDDT from PDB C-alpha records and groups contiguous runs below 50. Low pLDDT may reflect intrinsic disorder, missing binding partners, alternate conformations, or model uncertainty; it is NOT independent evidence that a region is disordered.

Returns model-local residue indices, observed PDB chain/residue identifiers, and heuristic linker/terminal/long-segment labels. A terminal label is relative to the modeled chain or fragment, not necessarily the full protein. PDB numbering is not mapped to full-length UniProt via SIFTS here.

This implementation is a reproducible screening heuristic, not a validated disorder predictor, biomolecular mechanism classifier, or clinical result. For background on intrinsic disorder, see Ruff & Pappu (2021), J Mol Biol. 433:167208; that paper does not validate these cutoffs or code.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`params`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.5.2Oct 14, 2026

changedInput schema / properties / params / properties / uniprot_id / description

Previous value: -"UniProt accession, e.g. 'P38398' (BRCA1)."New value: +"UniProt accession (6/10 characters), optionally with isoform suffix (e.g. P04637-2)."

changedInput schema / properties / params / properties / uniprot_id / pattern

Previous value: -"^[A-Z][0-9][A-Z0-9]{3}[0-9](?:[A-Z][0-9][A-Z0-9]{3}[0-9])?$"New value: +"^(?:[OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9](?:[A-Z][A-Z0-9]{2}[0-9]){1,2})(?:-[1-9][0-9]*)?$"

First observedv1.1.8May 29, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, closed-world), and the description goes well beyond them: it discloses the underlying data source (per-residue AlphaFold pLDDT from PDB C-alpha), the exact threshold (runs below 50), the alternative explanations for low pLDDT, the fact that terminal labels are relative to the modeled fragment, and that numbering is not SIFTS-mapped to UniProt.

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

Conciseness3/5

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

Purpose is front-loaded in the first sentence, which is good. But the body runs to six paragraphs of overlapping disclaimers ('not a validated disorder predictor, biomolecular mechanism classifier, or clinical result'), and the closing citation to Ruff & Pappu does not help an agent decide whether or how to invoke the tool.

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?

For a single-parameter, read-only tool with an output schema, the description supplies everything needed: what it reads, how it thresholds, what it returns (model-local indices, PDB identifiers, heuristic labels), and the interpretive limits of the result. Return values are also covered by the output schema.

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

Parameters3/5

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

One parameter with 0% schema description coverage, so the description must carry the burden. It conveys the input is a UniProt accession and that output numbering is not SIFTS-mapped to full-length UniProt, which clarifies the input/output relationship, but it never restates the accepted accession format or isoform suffix handling that the pattern encodes.

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

Purpose4/5

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

The opening sentence gives a specific verb and resource ('Flag low-confidence modeled regions as intrinsic-disorder candidates') and the following text pins down the mechanism: pLDDT from PDB C-alpha records, contiguous runs below 50. It does not name or contrast itself with any sibling tool (e.g. analyze_structural_confidence), so it is clear but not sibling-differentiating.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the agent can infer this is a screening step for disorder candidates, and the description warns that low pLDDT is NOT independent evidence of disorder and that this is not a validated predictor. However, there is no explicit 'use this when / use X instead' guidance and no named alternative.

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