# .env ファイル例
PINECONE_API_KEY=your-api-key-here
PINECONE_INDEX_NAME=your-index-name
PINECONE_ENVIRONMENT=gcp-starter

import { tool } from "@modelcontextprotocol/runtime";
import { PineconeClient } from "@pinecone-database/pinecone";

// Pineconeクライアント初期化
const pinecone = new PineconeClient();
await pinecone.init({
  apiKey: process.env.PINECONE_API_KEY,
  environment: process.env.PINECONE_ENVIRONMENT
});

const index = pinecone.Index(process.env.PINECONE_INDEX);

// セマンティック検索ツール
export const semanticSearch = tool({
  name: "semantic-search",
  description: "意味的な検索を実行する",
  parameters: {
    query: {
      type: "string",
      description: "検索クエリ"
    },
    top_k: {
      type: "number",
      description: "取得する結果の数",
      default: 5
    },
    filter: {
      type: "object",
      description: "メタデータフィルター",
      optional: true
    }
  },
  handler: async ({ query, top_k, filter }) => {
    // 埋め込みベクトル生成
    const embedding = await generateEmbedding(query);
    
    // Pinecone検索実行
    const results = await index.query({
      vector: embedding,
      topK: top_k,
      filter: filter,
      includeMetadata: true
    });
    
    return results.matches.map(match => ({
      id: match.id,
      text: match.metadata.text,
      metadata: match.metadata,
      score: match.score
    }));
  }
});