Skip to main content
Glama

Predict Structure Boltz2

predict_structure_boltz2
Read-only

Predict biomolecular structures: use direct multimolecular prediction for protein, ligand, DNA, RNA complexes, or a UniProt-to-docking workflow for protein-ligand complexes.

Instructions

Boltz-2 structure workflow. Use mode='structure' for direct multimolecular structure prediction or mode='protein_ligand' for the integrated UniProt-to-docking workflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoBoltz-2 workflow mode.structure
protein_sequencesNoProtein sequences for direct Boltz-2 prediction.
ligand_smilesNoLigand SMILES strings.
dna_sequencesNoOptional DNA sequences for complex prediction.
rna_sequencesNoOptional RNA sequences for complex prediction.
uniprot_accessionNoUniProt accession used when mode='protein_ligand'.
predict_affinityNoPredict ligand binding affinity when ligands are present.
method_conditioningNoOptional structure-style conditioning.x-ray
pocket_residuesNoOptional binding-pocket residue constraints.
recycling_stepsNoBoltz-2 recycling iterations. Default 3.
sampling_stepsNoDiffusion sampling steps. Default 200.
diffusion_samplesNoNumber of structural hypotheses. Default 1.
Behavior3/5

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

Annotations already declare readOnlyHint=true, and description adds mode context. However, it does not disclose limitations, input conflicts, or output behavior beyond schema info.

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?

Two clear sentences that are front-loaded and efficient, with no wasted words.

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

Completeness2/5

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

With 12 parameters and no output schema, the description is too sparse. It does not cover parameter semantics for complex inputs like pocket_residues or the interaction between multiple sequence types.

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?

Schema coverage is 100%, so baseline 3. The description adds minimal meaning beyond schema by explaining modes, but does not clarify parameter interactions (e.g., protein_sequences vs uniprot_accession).

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 description clearly states it is a Boltz-2 structure workflow with two modes (structure and protein_ligand), distinguishing it from sibling tools like get_alphafold_structure. However, it could be more specific about the output format.

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?

The description instructs which mode to use for multimolecular vs. protein-ligand docking, but lacks explicit guidance on when not to use this tool or comparisons to alternatives like AlphaFold.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SachinGawande2003/Heuris-BioMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server