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Provides intelligent memory management capabilities using Qdrant vector database for semantic search and storage.
Empowers AI assistants to access and analyze comprehensive financial data, stock information, company fundamentals, and market insights.
Exposes a local SQLite database and LanceDB vector database containing information on Chicago Public Schools.
Executes PySpark code via a Model Context Protocol (MCP) server.
Access content from MediaWiki-based websites through the Model Context Protocol to ground AI responses.
Establishes a ChromaDB-based local knowledge base system supporting text and PDF documents for vectorized storage and efficient similarity retrieval.
Facilitates communication between AI models and external resources using the Model Context Protocol.
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