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    Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.
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    MIT
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    Enables searching for any text within a specified Algolia index through an MCP-compatible interface. It allows users to integrate Algolia search capabilities into their environment using an application ID and API key.
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    MIT
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    A server enabling seamless interaction between AI models and WordPress sites with secure, standardized communication using the WordPress REST API for comprehensive site management.
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    MIT
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    MCP server for semantic search across the complete ObjectARX 2026 documentation set. Indexes 89,715 text chunks from 22 guides in ChromaDB with hybrid BM25 + dense retrieval.
    MIT
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    Enables conversational AI to access, analyze, and interact with Associated Press news content through natural language, with 26 tools for search, trends, and content monitoring.
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    MIT
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    A vendor-neutral, release-aware context contract and MCP runtime that provides reliable data agents with compact metadata, semantic definitions, and validated SQL compilation.
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    MIT
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    A comprehensive Data Platform server that enables seamless integration between PostgreSQL databases and MinIO object storage, with AI-powered natural language query capabilities.
    MIT
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    Enables searching local Korean HWP/HWPX documents via Codex or Claude Code by indexing them with a free multilingual embedding model, keeping documents and indexes locally without requiring an API key.
    MIT
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    A privacy-first personal context engine that ingests personal photos and message exports, extracts cited facts, and serves a queryable profile over MCP for natural-language questions like 'when did I last see Sarah?'.
    MIT
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    FEGIS is a Model Context Protocol server that gives LLMs structured, persistent and portable memory through customizable cognitive tools defined in schema.
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    Python
    MIT
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    Enables querying of live organizational data (student records, outcomes, certifications, finances, donations, communications) via Claude using structured database queries and semantic search.
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    Enables secure querying of analytics data stored in AWS Athena/S3 through natural language, with multiple security layers including query validation, resource limits, and automatic PII redaction to prevent data breaches and destructive operations.
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    Enables AI assistants to crawl websites, extract and store web content with semantic search capabilities using vector embeddings, and retrieve information through natural language queries with tag-based filtering and intelligent content cleaning.