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"Connecting Cursor to Oracle Database for Data Learning" matching MCP servers:

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    Enables GitHub Copilot and other LLMs to execute read-only SQL queries against Oracle databases with secure connection pooling and schema introspection capabilities.
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    AGPL 3.0
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    MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.
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    MIT
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    Enables AI tools to interact with Oracle databases through query execution, schema browsing, stored procedure calls, and transaction management. Supports multiple database connections with safety features like read-only mode and dangerous query detection.
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    MIT
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    Provides flexible access to Oracle databases for AI assistants like Claude, supporting SQL queries across multiple schemas with comprehensive database introspection capabilities.
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    MIT
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    An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.
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    MIT
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    An extensible MCP server for database operations that supports PostgreSQL for managing schemas, tables, data, and user permissions. It features automatic migration recording for DDL changes and integrates with various AI-powered editors like Cursor, Zed, and Claude Code.
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    MIT
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    Provides a natural language interface for querying and managing PostgreSQL, MySQL, MariaDB, MSSQL, and SQLite databases using the Model Context Protocol. Users can explore database schemas and visualize query results through an integrated web dashboard.
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    MIT
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    A Model Context Protocol server that provides contextual Oracle database schema information, enabling AI assistants to understand and work with large databases containing thousands of tables.
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    MIT
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    Provides universal database operations for AI assistants through MCP, supporting 40+ databases including PostgreSQL, MySQL, MongoDB, Redis, and SQLite with built-in introspection tools for schema exploration.
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    MIT
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    MCP server for multiple databases (PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis) with tools for schema inspection, querying, performance diagnostics, and safe write operations, featuring access modes, PII masking, and audit logging.
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    Apache 2.0
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    Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.
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    Provides contextual Oracle database schema information to AI assistants, enabling them to understand and work with large databases containing thousands of tables. Supports multi-database connections, smart schema caching, table lookups, and relationship mapping.
    Last updated