OceanBase 데이터베이스와의 안전한 상호작용을 지원하는 모델 컨텍스트 프로토콜(MCP) 서버입니다. 이 서버를 통해 AI 비서가 제어된 인터페이스를 통해 테이블을 나열하고, 데이터를 읽고, SQL 쿼리를 실행할 수 있으므로 데이터베이스 탐색 및 분석이 더욱 안전하고 체계적으로 이루어집니다.
사용 가능한 OceanBase 테이블을 리소스로 나열합니다.
표의 내용을 읽어보세요
적절한 오류 처리를 통해 SQL 쿼리 실행
환경 변수를 통한 안전한 데이터베이스 액세스
종합 로깅
Related MCP server: Microsoft SQL Server MCP Server
지엑스피1
다음 환경 변수를 설정하세요.
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_databaseclaude_desktop_config.json 에 다음을 추가하세요:
{
"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
pytest환경 변수나 자격 증명을 커밋하지 마십시오.
최소한의 필수 권한이 있는 데이터베이스 사용자를 사용하세요
프로덕션 사용을 위해 쿼리 허용 목록을 구현하는 것을 고려하세요.
모든 데이터베이스 작업을 모니터링하고 기록합니다.
이 MCP 서버가 작동하려면 데이터베이스 액세스가 필요합니다. 보안을 위해:
최소한의 권한으로 전담 OceanBase 사용자를 만듭니다.
루트 자격 증명이나 관리 계정을 사용하지 마십시오.
필요한 작업에만 데이터베이스 액세스를 제한합니다.
감사 목적으로 로깅을 활성화합니다 .
데이터베이스 접근에 대한 정기적인 보안 검토
자세한 지침은 OceanBase 보안 구성 가이드를 참조하세요.
제한된 OceanBase 사용자 생성
적절한 권한 설정
데이터베이스 액세스 모니터링
보안 모범 사례
⚠️ 중요: 데이터베이스 액세스를 구성할 때는 항상 최소 권한 원칙을 따르세요.
Apache 라이센스 - 자세한 내용은 LICENSE 파일을 참조하세요.
저장소를 포크하세요
기능 브랜치를 생성합니다( git checkout -b feature/amazing-feature )
변경 사항을 커밋하세요( git commit -m 'Add some amazing feature' )
브랜치에 푸시( git push origin feature/amazing-feature )
풀 리퀘스트 열기
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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