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AWS RDS MCP(Model Context Protocol) server for monitoring and analyzing RDS(MySQL, PostgreSQL) instances and it's perfor
A Model Context Protocol (MCP) server for monitoring and analyzing Amazon RDS(MySQL, PostgreSQL) instances information, metrics and slowquery logs.
Install directly from GitHub using pipx:
# Install
pipx install git+https://github.com/neoai-agent/rds-mcp.git
# Or run without installation
pipx run git+https://github.com/neoai-agent/rds-mcp.git
The server supports multiple AWS authentication methods:
When running on AWS infrastructure with IAM roles attached, you can omit AWS credentials:
rds-mcp --openai-api-key "YOUR_OPENAI_API_KEY" --region "YOUR_AWS_REGION"
For local development or when IAM roles are not available:
rds-mcp --access-key "YOUR_AWS_ACCESS_KEY" --secret-access-key "YOUR_AWS_SECRET_KEY" --region "YOUR_AWS_REGION" --openai-api-key "YOUR_OPENAI_API_KEY"
You can also set AWS credentials via environment variables:
rds-mcp --access-key "YOUR_AWS_ACCESS_KEY" --secret-access-key "YOUR_AWS_SECRET_KEY" --region "YOUR_AWS_REGION" --openai_api_key "YOUR_OPENAI_API_KEY"
Note: When using IAM roles, the server will automatically use the default AWS credential chain, which includes IAM roles, environment variables, and AWS credentials file.
The server provides the following tools for RDS instance management and monitoring:
await get_db_info(
database_name="your-db-instance",
region="your-aws-region"
)
await get_database_metrics(
database_name="your-db-instance",
time_range_minutes=30
)
await get_database_queries(
database_name="your-db-instance",
time_range_minutes=30
)
await get_top_rds_load(
database_name="your-db-instance",
time_range_minutes=30
)
For development setup:
git clone https://github.com/neoai-agent/rds-mcp.git
cd rds-mcp
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -e ".[dev]"
MIT License - See LICENSE file for details
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