// src/tools.ts
import { Tool } from '@modelcontextprotocol/sdk/types.js';
/**
* MCP Tool Definitions for AlphaGenome Server
*/
export const PREDICT_VARIANT_TOOL: Tool = {
name: 'predict_variant_effect',
description: `Predict the regulatory impact of a genetic variant using AlphaGenome AI.
Powered by Google DeepMind's AlphaGenome model for accurate regulatory predictions.
Analyzes how a single nucleotide change affects:
- Gene expression (RNA-seq predictions)
- Splicing patterns
- Transcription factor binding
- Chromatin accessibility
- Histone modifications
Perfect for: variant interpretation, GWAS follow-up, clinical genomics research.
Example: "Analyze chr17:41234567A>T with AlphaGenome"`,
inputSchema: {
type: 'object',
properties: {
chromosome: {
type: 'string',
description: 'Chromosome (chr1-chr22, chrX, chrY)',
pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$',
},
position: {
type: 'number',
description: 'Genomic position (1-based, positive integer)',
minimum: 1,
},
ref: {
type: 'string',
description: 'Reference allele (A, T, G, or C)',
pattern: '^[ATGCatgc]+$',
},
alt: {
type: 'string',
description: 'Alternate allele (A, T, G, or C)',
pattern: '^[ATGCatgc]+$',
},
output_types: {
type: 'array',
items: {
type: 'string',
enum: [
'rna_seq',
'cage',
'splice',
'histone',
'tf_binding',
'dnase',
'atac',
'contact_map',
],
},
description: 'Optional: specific analyses to run (default: all)',
},
tissue_type: {
type: 'string',
description: 'Optional: tissue context (UBERON term, e.g., "UBERON:0001157" for brain)',
},
},
required: ['chromosome', 'position', 'ref', 'alt'],
},
};
export const ANALYZE_REGION_TOOL: Tool = {
name: 'analyze_region',
description: `Analyze regulatory elements in a genomic region using AlphaGenome AI.
Powered by Google DeepMind's AlphaGenome model for regulatory element discovery.
Identifies:
- Promoters and their strength
- Enhancers and target genes
- Silencers
- Transcription factor binding sites
- Chromatin states
Perfect for: finding regulatory hotspots, understanding gene regulation, targeting for CRISPR.
Size limits: 1kb minimum, 1Mb maximum (optimal: 10-100kb)
Example: "Find regulatory elements in chr11:5225464-5227071"`,
inputSchema: {
type: 'object',
properties: {
chromosome: {
type: 'string',
description: 'Chromosome (chr1-chr22, chrX, chrY)',
pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$',
},
start: {
type: 'number',
description: 'Start position (1-based)',
minimum: 1,
},
end: {
type: 'number',
description: 'End position (must be > start + 1000)',
minimum: 1,
},
analysis_types: {
type: 'array',
items: {
type: 'string',
enum: ['promoter', 'enhancer', 'silencer', 'tf_binding', 'chromatin_state'],
},
description: 'Optional: specific element types to find (default: all)',
},
resolution: {
type: 'string',
enum: ['base', 'window'],
description: 'Resolution: "base" (1bp) or "window" (128bp). Default: base',
},
},
required: ['chromosome', 'start', 'end'],
},
};
export const BATCH_SCORE_TOOL: Tool = {
name: 'batch_score_variants',
description: `Score and prioritize multiple genetic variants using AlphaGenome AI.
Powered by Google DeepMind's AlphaGenome model for high-throughput variant scoring.
Analyzes up to 100 variants simultaneously and ranks them by regulatory impact.
Scoring metrics:
- rna_seq: Gene expression changes
- splice: Splicing alterations
- regulatory_impact: Combined regulatory score
- combined: All metrics weighted
Perfect for: GWAS post-analysis, VCF filtering, variant prioritization.
Example: "Score these 50 variants and show me the top 10 by regulatory impact"`,
inputSchema: {
type: 'object',
properties: {
variants: {
type: 'array',
items: {
type: 'object',
properties: {
chromosome: {
type: 'string',
description: 'Chromosome',
pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$',
},
position: {
type: 'number',
description: 'Position',
minimum: 1,
},
ref: {
type: 'string',
description: 'Reference allele',
pattern: '^[ATGCatgc]+$',
},
alt: {
type: 'string',
description: 'Alternate allele',
pattern: '^[ATGCatgc]+$',
},
variant_id: {
type: 'string',
description: 'Optional: variant identifier (e.g., rs number)',
},
},
required: ['chromosome', 'position', 'ref', 'alt'],
},
description: 'List of variants to analyze (1-100)',
minItems: 1,
maxItems: 100,
},
scoring_metric: {
type: 'string',
enum: ['rna_seq', 'splice', 'regulatory_impact', 'combined'],
description: 'Metric to use for scoring and ranking',
},
top_n: {
type: 'number',
description: 'Number of top variants to return (default: 10, max: 100)',
minimum: 1,
maximum: 100,
},
include_interpretation: {
type: 'boolean',
description: 'Include detailed clinical interpretation (default: false)',
},
},
required: ['variants', 'scoring_metric'],
},
};
/**
* All available tools
*/
export const ALL_TOOLS: Tool[] = [PREDICT_VARIANT_TOOL, ANALYZE_REGION_TOOL, BATCH_SCORE_TOOL];
