AlphaFold Sovereign MCP

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Score Binding Pocket Geometry

score_binding_pocket_geometry

Read-onlyIdempotent

Detect and score putative binding pockets from AlphaFold coordinates with a geometry-only heuristic for reproducible pre-screening without ML models.

Instructions

Identify and score putative binding pockets from AlphaFold geometry.

Detects pockets with a geometry-only heuristic. Residues in the inner 60 percent of the structure by distance from the centroid are taken as the pocket-forming core, then grown greedily into clusters within an 8 Angstrom radius. A cluster is kept as a putative pocket when it has at least min_pocket_residues members and a mean pLDDT of at least 50.

Each pocket reports a radius of gyration (compactness of the pocket residues), a centroid offset (distance of the pocket centroid from the structure centroid; larger means more peripheral), mean pLDDT, and an uncalibrated geometry score. Centroid offset does not measure solvent exposure, cavity validity, or ligand binding. The druggability index runs 0 to 100 and is the sum of four equally weighted 0 to 25 sub-scores: residue count, radius of gyration, mean pLDDT, and centroid offset.

This is a fast, dependency-free pre-screen, not a substitute for a validated pocket detector such as fpocket or P2Rank. It needs no ML model, is fully reproducible from AlphaFold coordinates, and runs in air-gapped deployments.

Input Schema

Name	Required	Description	Default
`params`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.5.2Oct 14, 2026

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

A4.3/5.0

Behavior5/5

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

Goes well beyond annotations by describing the pocket-detection heuristic, residue thresholds, cluster growth, pLDDT cutoff, reported metrics, uncalibrated scoring, and limitations such as centroid offset not measuring solvent exposure or ligand binding. This gives the agent rich behavioral context for a read-only, idempotent computation.

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

Conciseness5/5

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

Front-loads the purpose, then moves efficiently through algorithm, output metrics, scoring, and limitations. The length is justified by the scientific complexity, and no sentence is wasted.

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 complex structural-bioinformatics scoring tool, the description is complete enough: annotations cover read-only/idempotent/closed-world behavior, an output schema exists, and the description explains the heuristic, thresholds, scoring, caveats, and intended use.

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?

The description clarifies that min_pocket_residues is a membership threshold for retaining a putative pocket, adding meaning beyond the schema field name. It does not explain the UniProt accession format, default/range behavior, or other parameter constraints, so compensation for low schema-description coverage is only partial.

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?

States a specific verb and resource: identifying and scoring putative binding pockets from AlphaFold geometry. It clearly scopes the tool as a geometry-only pre-screen, though it does not explicitly distinguish it from related siblings such as assess_target_druggability.

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

Usage Guidelines4/5

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

Gives clear usage context: a fast, dependency-free, reproducible pre-screen for AlphaFold coordinates, not a substitute for validated pocket detectors like fpocket or P2Rank. It does not, however, name sibling tools or explicitly state when to choose this over assess_target_druggability.

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