OceanBase

OceanBase is an MCP server collection that connects AI assistants to OceanBase distributed relational databases and its surrounding operational ecosystem. Database administrators, data engineers, and developers use this server collection to execute SQL statements, automate operational workflows, and administer database infrastructure through conversational AI interfaces. The project encompasses several distinct servers covering various layers of the OceanBase ecosystem. This includes the primary OceanBase MCP Server for executing queries and managing database records, the OCP MCP Server for interacting with OceanBase Cloud Platform to monitor clusters, and the OBCloud MCP Server for managing cloud-hosted instances. Additionally, it integrates Kubernetes management via the OKCTL MCP Server, provides diagnostic and troubleshooting capabilities through the OBDIAG MCP Server, and manages cluster deployments via obshell. Specialized modules such as seekdb for vector operations and PowerMem for memory retention and retrieval are also supported, enabling natural language control across the entire database management and lifecycle spectrum.

Category: Databases & Data Stores

Tags: distributed-database, oceanbase, relational-database, SQL

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How to install and configure OceanBase

1. Ensure you have Python 3.8+ or TypeScript 5.0+ installed on your system, along with access to an active OceanBase database instance. 2. Clone the repository locally or navigate to the official repository at https://github.com/oceanbase/mcp-oceanbase. 3. Browse to the specific MCP server directory you wish to use (such as src/oceanbase_mcp_server, src/ocp_mcp_server, or src/obcloud_mcp_server). 4. Review the dedicated README file inside that directory for exact environment variables, dependencies, and configuration parameters. 5. Configure your MCP client configuration file (such as Claude Desktop or Cursor) by adding the target OceanBase server command, arguments, and required database connection credentials. 6. Restart your MCP client to initialize the connection.

What you can do with OceanBase

• Execute and validate complex SQL queries against distributed OceanBase databases using natural language prompts in AI assistants. - Monitor OceanBase cluster performance metrics and operational health by integrating with OceanBase Cloud Platform via the OCP server. - Manage and provision cloud-hosted database instances directly through OBCloud service integration from conversational interfaces. - Orchestrate and troubleshoot OceanBase deployments and resource configurations across Kubernetes environments using the OKCTL module. - Perform automated database root cause analysis and diagnostic reviews utilizing OBDIAG diagnostic tooling capabilities.

Key facts

• Open Source
• https://github.com/oceanbase/mcp-oceanbase
• Databases & Data Stores
• distributed-database, oceanbase, relational-database, SQL

Part of MCP Servers

What is OceanBase MCP?

OceanBase MCP is a collection of Model Context Protocol servers built for the OceanBase ecosystem. It allows AI assistants like Claude to execute SQL queries, manage database resources, handle cloud instances, orchestrate Kubernetes deployments, and perform diagnostics using standardized tool protocols.

What tools are included in the OceanBase MCP repository?

The repository includes dedicated MCP servers for core OceanBase SQL operations, OceanBase Cloud Platform management, OBCloud cloud instances, OKCTL for Kubernetes, OBDIAG for performance diagnostics, obshell for cluster operations, seekdb for vector search, and PowerMem for memory management.

Which MCP clients work with OceanBase?

OceanBase MCP functions with standard Model Context Protocol clients. Users can configure and run these servers with AI assistants and developer tools including Claude Desktop, Cursor, and ChatGPT-compatible MCP environments that support local or custom server configurations.

Is OceanBase MCP open source?

Yes, OceanBase MCP is an open source project. It is licensed under the Apache License 2.0 and its full source code, documentation, and configuration guides are publicly accessible on GitHub.