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AlphaFold Sovereign MCP

AlphaFold Sovereign MCP

by smaniches
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Analyze Structural Confidence (pLDDT + PAE)

analyze_structural_confidence
Read-onlyIdempotent

Assess AlphaFold model reliability by summarizing pLDDT confidence and PAE uncertainty, including domain boundaries and druggability limitations, from a UniProt accession.

Instructions

Analyze AlphaFold structural confidence using pLDDT and PAE.

Returns a structural reliability summary (not a per-residue profile):

  • pLDDT: the model's mean confidence (AlphaFold DB globalMetricValue) plus a coarse confidence tier

  • PAE (predicted aligned error): mean and max inter-residue uncertainty and PAE-derived domain boundaries

  • Druggability pre-screen: model confidence limitations; actual ordered fraction and ligand suitability are NOT assessed

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "params": "<params>"
    },
    "name": "analyze_structural_confidence"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.5.2
    • 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])?$"New value: +"^(?:[OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9](?:[A-Z][A-Z0-9]{2}[0-9]){1,2})(?:-[1-9][0-9]*)?$"
  2. First observedv1.1.8

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld), and the description adds real value beyond them: it names the upstream data source ('AlphaFold DB globalMetricValue'), discloses that output is a summary rather than per-residue, and flags the pre-screen's limitations. What it omits is failure behavior for accessions without AlphaFold models, which matters for an openWorld remote lookup.

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?

One framing sentence plus three tight bullets, each earning its place; the scope caveat (summary, not per-residue) is front-loaded before the enumeration. No filler or restatement of the title.

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

Completeness4/5

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

An output schema exists, so the description does not need to document return shapes — yet it still gives enough of the result structure and limits to set expectations. The only real gap is the absence of any mention of the required input identifier or of what happens when a structure is unavailable.

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 never mentions the single required input (UniProt accession) or the isoform-suffix form; the schema's own property description carries that load. With reported coverage at 0%, the description does not compensate — but the parameter is a single, semantically obvious identifier, so the gap is modest rather than disabling.

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 and resource ('Analyze AlphaFold structural confidence using pLDDT and PAE') and immediately scopes the output ('structural reliability summary, not a per-residue profile'). This distinguishes it from neighbours like get_protein_structure, score_binding_pocket_geometry and assess_target_druggability without requiring the schema.

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?

The 'Druggability pre-screen' bullet explicitly declares what is NOT assessed ('ordered fraction and ligand suitability'), which implicitly routes the agent to assess_target_druggability for that work. However, it never states when to pick this over get_protein_structure or detect_intrinsically_disordered, so the routing guidance is partial rather than complete.

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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