summary
Pack: alphafold · Connect: https://pipeworx.io/mcp (see Connect below for a single-pack URL)
No MCP client? Call it directly: GET https://gateway.pipeworx.io/v1/tools/summary for the schema, then POST the same URL with its arguments for the data.
Short summary for a prediction (organism, sequence, mean pLDDT).
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
qualifier | string | yes |
Example call
Arguments
{
"qualifier": "P00533"
}
curl
curl -X POST https://gateway.pipeworx.io/alphafold/mcp \
-H 'Content-Type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"summary","arguments":{"qualifier":"P00533"}}}'
TypeScript (@pipeworx/sdk)
import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();
const result = await pipeworx.call('summary', {
"qualifier": "P00533"
});
More examples
{
"qualifier": "Q9Y5K6"
}
Response shape
| Field | Type | Description |
|---|---|---|
uniprot_entry | object | |
structures | array |
Full JSON Schema
{
"type": "object",
"properties": {
"uniprot_entry": {
"type": "object",
"properties": {
"ac": {
"type": "string"
},
"id": {
"type": "string"
},
"uniprot_checksum": {
"type": "string"
},
"sequence_length": {
"type": "number"
},
"segment_start": {
"type": "number"
},
"segment_end": {
"type": "number"
}
}
},
"structures": {
"type": "array",
"items": {
"type": "object",
"properties": {
"summary": {
"type": "object",
"properties": {
"model_identifier": {
"type": "string"
},
"model_category": {
"type": "string"
},
"model_url": {
"type": "string"
},
"model_format": {
"type": "string"
},
"model_type": {
"type": "null"
},
"model_page_url": {
"type": "string"
},
"provider": {
"type": "string"
},
"number_of_conformers": {
"type": "null"
},
"ensemble_sample_url": {
"type": "null"
},
"ensemble_sample_format": {
"type": "null"
},
"created": {
"type": "string"
},
"sequence_identity": {
"type": "number"
},
"uniprot_start": {
"type": "number"
},
"uniprot_end": {
"type": "number"
},
"coverage": {
"type": "number"
},
"experimental_method": {
"type": "null"
},
"resolution": {
"type": "null"
},
"confidence_type": {
"type": "string"
},
"confidence_version": {
"type": "null"
},
"confidence_avg_local_score": {
"type": "number"
},
"oligomeric_state": {
"type": "string"
},
"preferred_assembly_id": {
"type": "null"
},
"entities": {
"type": "array",
"items": {
"type": "object",
"properties": {
"entity_type": {
"type": "string"
},
"entity_poly_type": {
"type": "string"
},
"identifier": {
"type": "string"
},
"identifier_category": {
"type": "string"
},
"description": {
"type": "string"
},
"chain_ids": {
"type": "array",
"items": {
"type": "string"
}
}
}
}
}
}
}
}
}
}
},
"description": "Summary of protein prediction"
}
Connect
Add this to your MCP client config — every tool in the catalog, including this one — or use one-click install buttons:
{
"mcpServers": {
"pipeworx": {
"url": "https://pipeworx.io/mcp"
}
}
}
Connect to just the alphafold pack
{
"mcpServers": {
"alphafold": {
"url": "https://gateway.pipeworx.io/alphafold/mcp"
}
}
}
See Getting Started for client-specific install steps.