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Oracle Embraces MCP, Giving AI Agents Access to Data Stored in Flagship Database
database

Oracle Embraces MCP, Giving AI Agents Access to Data Stored in Flagship Database

Oracle integrates Model Context Protocol (MCP) to allow AI agents seamless, secure access to data in its flagship database platform.

July 29, 2025
5 min read
Tom Smith

Oracle integrates Model Context Protocol (MCP) to allow AI agents seamless, secure access to data in its flagship database platform.

Oracle Embraces MCP, Giving AI Agents Access to Data Stored in Flagship Database

Given its massive footprint in the enterprise computing market, there’s arguably no more important data source that AI agents and copilots must connect to than the Oracle database. That’s why Oracle’s embrace of the Model Context Protocol, or MCP — which adds context to a Large Language Model by enabling that LLM to interact directly with a data source in a standard format — is so important. Oracle is providing that support in the form of MCP Server for Oracle Database, which integrates MCP support into its core developer tools, making its flagship database accessible on any AI platform supporting MCP. MCP Server for Oracle Database, the first MCP deliverable from Oracle, makes integration possible through the Oracle Database command line interface. OracleSQLcl ships with tools including the Oracle SQL Server Developer extension for VS Code. OracleSQLcl provides MCP functionality that allows an AI assistant to securely connect to Oracle Database, managing credentials and running SQL database queries and scripts. Software requirements for using the MCP server include:
  • An Oracle Database
  • Oracle SQLcl with one or more defined database connections
  • User’s preferred development environment and LLM
  • When setting up MCP Server for Oracle Database, the company emphasized two security protections that database admins should follow:
  • Enable the least privileges that will enable users to accomplish their required tasks, thereby limiting the data that’s accessible to the LLM.
  • Use a sanitized, read-only replica or a data subset (instead of providing access to production databases for the LLM), while also conducting regular audits of LLM queries to discover anomalies or attempts to access restricted data.
  • New Functionality

    By tapping into an Oracle Database through MCP, users can ask for help performing database functions in their native language, which LLMs can use to generate SQL to complete the users’ requests. Developers will be able to use agentic workflows to run AI-generated SQL statements on an Oracle Database and then interact with the results, as opposed to having AI provide SQL for them to manage. Users can also utilize their preferred AI platform to explore their Oracle Database and the data it stores, and even have the AI platform explain the data to them.

    Potential Use Case

    Oracle outlined a way that a user or developer might deploy its new MCP Server. A user who has personal or corporate access to MCP server might ask their AI assistant to provide details on what’s stored in a dataset within an Oracle database as well as the type of data. The LLM has been trained to explore the database’s data dictionary by asking for permission and querying user tables. The LLM also wants to run SQL on behalf of the requesting user to satisfy the request for details on the types of data stored there. The user is asked to approve actions and queries; OracleSQLcl provides transparency into the activities of the LLM inside the database.

    Closing Thoughts

    Oracle’s endorsement, and delivery of a server for access to its flagship database, is another critical development adding to MCP’s momentum as a standard for connecting AI tools and data sources in a standard format. As one of the dominant database platforms, the importance of Oracle’s product, as well as its endorsement of this standard, can’t be overstated. The new Oracle server continues the trend of industry titans rallying behind MCP for the benefit of customers looking to unlock sophisticated, multivendor AI workflows.
    Source: Originally published at Cloud Wars on July 29, 2025.

    Frequently Asked Questions (FAQ)

    What is the Model Context Protocol (MCP)?

    The Model Context Protocol (MCP) is a standard format that allows Large Language Models (LLMs) to interact directly with data sources, thereby adding context to the LLM's responses.

    What is MCP Server for Oracle Database?

    MCP Server for Oracle Database is Oracle's implementation that integrates MCP support into its core developer tools, making Oracle Database accessible to any AI platform that supports MCP.

    How does MCP Server for Oracle Database enable AI agent access?

    It allows AI assistants to securely connect to Oracle Database, manage credentials, and run SQL queries and scripts through the Oracle Database command line interface, specifically using OracleSQLcl.

    What are the software requirements for using MCP Server for Oracle Database?

    The requirements include an Oracle Database, Oracle SQLcl with defined database connections, and the user's preferred development environment and LLM.

    What security measures are recommended when using MCP Server for Oracle Database?

    It is recommended to enable the least privileges for users and to use a sanitized, read-only replica or a data subset instead of production databases, along with regular audits of LLM queries.

    How can developers benefit from this integration?

    Developers can use agentic workflows to run AI-generated SQL statements directly on an Oracle Database and interact with the results, rather than just receiving AI-generated SQL.

    Can AI agents explain data stored in Oracle Database?

    Yes, users can leverage their preferred AI platform to explore their Oracle Database, understand the data it stores, and have the AI platform explain it to them.

    Crypto Market AI's Take

    Oracle's adoption of the Model Context Protocol (MCP) marks a significant stride in enabling AI agents to interact seamlessly with enterprise data. This development is particularly relevant in the financial sector, where secure and efficient data access is paramount. For businesses looking to leverage AI for market analysis or trading, connecting to robust data sources like Oracle databases is crucial. Our platform at Crypto Market AI focuses on providing advanced AI-driven tools for cryptocurrency trading and market intelligence, and we recognize the importance of such interoperability standards for unlocking sophisticated, multi-vendor AI workflows. This integration by Oracle further validates the growing trend of AI agents becoming integral to data-driven decision-making across various industries.

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