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securityF
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qualityEnables LLMs to perform statistical analysis and generate ML predictions on user data from databases or CSV files through a Model Context Protocol server.
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Python
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Why this server?
Enables LLMs to perform statistical analysis and generate ML predictions on user data from databases or CSV files.
Why this server?
Allows users to analyze event log data from PostgreSQL databases through natural language interfaces.
Why this server?
Allows users to query and export data from multiple relational databases (MySQL, PostgreSQL, Oracle, SQLite, etc.) in read-only mode.
Why this server?
Enables users to upload retail data, analyze trends, optimize inventory, and forecast sales using AI-powered insights.
Why this server?
Enhances the MCP memory server by implementing PouchDB for robust document storage and enabling the creation and management of a knowledge graph.
Why this server?
Connects agents to Elasticsearch data using the Model Context Protocol, allowing natural language interaction with Elasticsearch indices.
Why this server?
Allows users to query and analyze Wazuh security logs stored in OpenSearch through natural language.
Why this server?
MCP Server for interacting with Cube semantic layers that provides tools for querying and describing data from Cube deployments.
Why this server?
Enables graph database interactions with Neo4j, allowing users to access and manipulate graph data through natural language commands.
Why this server?
A server that enables language models to perform web searches through SearXNG using the Model Context Protocol standard.