mcp-talent-server/dist/tools/vector-search.js

Model Context Protocol server for talent management tools

import { z } from 'zod';
import { rateSheet2025VectorStore } from '../services/vector-store.js';
const VectorSearchInput = z.object({
    query: z.string().min(1, "Search query is required")
        .describe("Natural language search query to find relevant content in the knowledge base"),
    limit: z.number().min(1).max(100).default(10),
});
export class VectorSearchTool {
    async search(input) {
        try {
            const validatedInput = VectorSearchInput.parse(input);
            const results = await rateSheet2025VectorStore.similaritySearch(validatedInput.query.trim(), validatedInput.limit);
            return results;
        }
        catch (error) {
            return {
                results: [],
            };
        }
    }
}
export const VectorSearchDescription = `**Vector Search Tool - Semantic Document & Knowledge Base Search**

**Primary Purpose**: Advanced semantic search across uploaded documents and talent rate cards using AI-powered embeddings.

**Core Capabilities**:
• **Semantic Understanding**: Finds conceptually related content, not just keyword matches
• **Multi-Document Search**: Searches across PDF, DOCX, TXT files simultaneously
• **Relevance Scoring**: Returns results with confidence scores (0-1 scale)
• **Content Highlighting**: Provides contextual snippets with key terms highlighted
• **Smart Filtering**: Filter by file type, user, relevance threshold, and date
• **Deduplication**: Groups results by document to avoid redundant chunks
• **Rich Metadata**: Includes document source, creation date, file type, and processing stats

**Specialized for Talent Management**:
• **Rate Card Search**: Find specific pricing for Instagram Stories, TikTok posts, YouTube integrations
• **Talent Discovery**: Search for influencers by niche, audience size, or platform specialization
• **Contract Information**: Locate terms, deliverables, and pricing structures
• **Performance Data**: Find engagement rates, reach statistics, and campaign results

**Advanced Features**:
• **Multi-criteria Filtering**: Combine relevance, date, file type, and user filters
• **Batch Processing**: Handle large document collections efficiently
• **Error Recovery**: Robust error handling with helpful suggestions
• **Search Analytics**: Provides processing time, match counts, and quality metrics

**Optimal Use Cases**:
✓ "Find Instagram Story rates for beauty influencers"
✓ "Show me YouTube integration pricing above $5000"
✓ "Search for talent contracts with exclusive clauses"
✓ "Find performance data for TikTok campaigns in Q3"
✓ "Locate audience demographics for fitness influencers"

**Important Note**:
- For searching for rates always search in Rate Sheet 2025 file vectors for accurate results.
- Always mention file name in the query to get accurate results.

example vector search queries:
- Denny kim rates in Rate Sheet 2025

**Parameters Guide**:
• query: Natural language search (required)
• limit: Number of results to return (default: 10, max: 100)

**Response Format**: Returns structured results with content snippets, relevance scores, source attribution, search statistics, and actionable suggestions for query refinement.

**Important Note**:
• This tool use pinecone vector store always use limit parameter to paginate the results and optimize the results and output tokens`;
export const vectorSearchSchema = VectorSearchInput;
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