一个模型上下文协议 (MCP) 服务器，用于实现与 OceanBase 数据库的安全交互。该服务器允许 AI 助手通过受控接口列出表格、读取数据并执行 SQL 查询，从而使数据库的探索和分析更加安全、结构化。
将可用的 OceanBase 表列为资源
读取表内容
执行 SQL 查询并进行适当的错误处理
通过环境变量保护数据库访问
综合日志记录
Related MCP server: Microsoft SQL Server MCP Server
pip install oceanbase-mcp-server设置以下环境变量：
OB_HOST=localhost # Database host
OB_PORT=2881 # Optional: Database port (defaults to 2881 if not specified)
OB_USER=your_username
OB_PASSWORD=your_password
OB_DATABASE=your_database将其添加到您的claude_desktop_config.json中：
{
"mcpServers": {
"oceanbase": {
"command": "uv",
"args": [
"--directory",
"path/to/oceanbase_mcp_server",
"run",
"oceanbase_mcp_server"
],
"env": {
"OB_HOST": "localhost",
"OB_PORT": "2881",
"OB_USER": "your_username",
"OB_PASSWORD": "your_password",
"OB_DATABASE": "your_database"
}
}
}
}# Install dependencies
pip install -r requirements.txt
# Run the server
python -m oceanbase_mcp_server# Clone the repository
git clone https://github.com/yourusername/oceanbase_mcp_server.git
cd oceanbase_mcp_server
# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install development dependencies
pip install -r requirements-dev.txt
# Run tests
pytest切勿提交环境变量或凭据
使用具有最低所需权限的数据库用户
考虑实施查询白名单以供生产使用
监控并记录所有数据库操作
此 MCP 服务器需要数据库访问权限才能运行。出于安全考虑：
创建具有最小权限的专用 OceanBase 用户
切勿使用根凭据或管理帐户
将数据库访问限制为仅进行必要的操作
启用日志记录以用于审计目的
定期对数据库访问进行安全审查
请参阅OceanBase 安全配置指南，详细了解：
创建受限的OceanBase用户
设置适当的权限
监控数据库访问
安全最佳实践
⚠️重要提示：配置数据库访问时始终遵循最小特权原则。
Apache 许可证 - 有关详细信息，请参阅 LICENSE 文件。
分叉存储库
创建你的功能分支（ git checkout -b feature/amazing-feature ）
提交您的更改（ git commit -m 'Add some amazing feature' ）
推送到分支（ git push origin feature/amazing-feature ）
打开拉取请求
Execute an SQL query on the OceanBase server
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The SQL query to execute |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions execution but fails to address critical aspects like required permissions, transaction handling, error behavior, or result format. This leaves significant gaps for a tool that performs database operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary elaboration. It's appropriately sized and front-loaded, with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a database execution tool with no annotations and no output schema, the description is insufficient. It lacks information about return values, error handling, security requirements, and operational constraints, which are critical for proper tool invocation in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'query' documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline for adequate but unenhanced documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('execute') and resource ('SQL query on the OceanBase server'), providing a specific verb+resource combination. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or limitations. It merely states what the tool does without context for application, leaving the agent to infer usage scenarios independently.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0execute_sqlScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'execute_sql' has a clear and distinct purpose that cannot be confused with any other tool in this set.
The single tool name 'execute_sql' follows a clear verb_noun pattern, and with only one tool, consistency is inherently perfect. There are no other tools to compare against, so no inconsistencies can exist.
A single tool is too few for a database server's apparent scope, which typically requires operations like querying, updating, schema management, and transaction handling. This minimal set severely limits functionality and will likely cause agent failures in complex tasks.
The tool surface is severely incomplete for a database server domain. It only provides SQL execution, missing essential operations such as listing tables, describing schemas, creating/dropping tables, managing transactions, or handling connections, leaving significant gaps that will hinder agent workflows.
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