AlphaGenome MCP Server

Instructions

Implementation Reference

• src/index.ts:242-248 (handler)

  MCP callTool request handler case that executes the tool by calling the AlphaGenomeClient method.

  case 'predict_allele_specific_effects': {
    const params = validateInput(variantPredictionSchema, args) as VariantPredictionParams;
    const result = await getClient().predictAlleleSpecificEffects(params);
    return {
      content: [{ type: 'text', text: JSON.stringify(result, null, 2) }],
    };
  }

• src/tools.ts:582-602 (schema)

  Tool schema definition including input validation schema, description, and name.

  export const PREDICT_ALLELE_SPECIFIC_EFFECTS_TOOL: Tool = {
    name: 'predict_allele_specific_effects',
    description: `Analyze allele-specific regulatory effects.
  
  Detailed analysis of how each allele affects gene regulation differently.
  
  Perfect for: ASE analysis, imprinting studies.
  
  Example: "Analyze allele-specific effects of chr15:67890123A>G"`,
    inputSchema: {
      type: 'object',
      properties: {
        chromosome: { type: 'string', pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$' },
        position: { type: 'number', minimum: 1 },
        ref: { type: 'string', pattern: '^[ATGCatgc]+$' },
        alt: { type: 'string', pattern: '^[ATGCatgc]+$' },
        tissue_type: { type: 'string' },
      },
      required: ['chromosome', 'position', 'ref', 'alt'],
    },
  };

• src/tools.ts:709-730 (registration)

  Registration of the tool in the ALL_TOOLS array exported for use in MCP listTools handler.

  export const ALL_TOOLS: Tool[] = [
    PREDICT_VARIANT_TOOL,
    BATCH_SCORE_TOOL,
    ASSESS_PATHOGENICITY_TOOL,
    PREDICT_TISSUE_SPECIFIC_TOOL,
    COMPARE_VARIANTS_TOOL,
    PREDICT_SPLICE_IMPACT_TOOL,
    PREDICT_EXPRESSION_IMPACT_TOOL,
    ANALYZE_GWAS_LOCUS_TOOL,
    COMPARE_ALLELES_TOOL,
    BATCH_TISSUE_COMPARISON_TOOL,
    PREDICT_TF_BINDING_IMPACT_TOOL,
    PREDICT_CHROMATIN_IMPACT_TOOL,
    COMPARE_PROTECTIVE_RISK_TOOL,
    BATCH_PATHOGENICITY_FILTER_TOOL,
    COMPARE_VARIANTS_SAME_GENE_TOOL,
    PREDICT_ALLELE_SPECIFIC_EFFECTS_TOOL,
    ANNOTATE_REGULATORY_CONTEXT_TOOL,
    BATCH_MODALITY_SCREEN_TOOL,
    GENERATE_VARIANT_REPORT_TOOL,
    EXPLAIN_VARIANT_IMPACT_TOOL,
  ];

• scripts/alphagenome_bridge.py:578-598 (handler)

  Core handler function implementing the allele-specific effects prediction by calculating ASE ratio from reference and alternate expression scores.

  def predict_allele_specific_effects(client, params: Dict[str, Any]) -> Dict[str, Any]:
      """Analyze allele-specific expression effects."""
      result = predict_variant_effect(client, params)
  
      rna_data = result['predictions'].get('rna_seq', {})
      ref_score = rna_data.get('reference_score', 0)
      alt_score = rna_data.get('alternate_score', 0)
  
      # Calculate allele-specific ratio
      if ref_score + alt_score > 0:
          ase_ratio = alt_score / (ref_score + alt_score)
      else:
          ase_ratio = 0.5
  
      return {
          'variant': result['variant'],
          'ref_expression': ref_score,
          'alt_expression': alt_score,
          'ase_ratio': float(ase_ratio),
          'interpretation': 'alt_biased' if ase_ratio > 0.6 else ('ref_biased' if ase_ratio < 0.4 else 'balanced')
      }

• src/alphagenome-client.ts:412-418 (helper)

  Helper client method that invokes the Python bridge for the tool execution.

  async predictAlleleSpecificEffects(params: VariantPredictionParams): Promise<any> {
    try {
      return await this.callPythonBridge('predict_allele_specific_effects', params);
    } catch (error) {
      if (error instanceof ApiError) throw error;
      throw new ApiError(`Allele-specific effects prediction failed: ${error}`, 500);
    }