About SkySQL MCP Server
SkySQL MCP Server is an MCP server and client repository for managing SkySQL MariaDB Cloud database instances. It supports instance operations, SQL execution, credential and IP allowlist management, and service monitoring.
Key features
- 01Launch and manage serverless MariaDB instances
- 02Interact with database agents
- 03Run SQL on SkySQL instances
- 04Manage credentials and IP allowlists
- 05List and monitor database services
Use cases
- 01Operate SkySQL databases through an agent
- 02Run SQL directly on a SkySQL instance
- 03Manage database credentials and IP access
- 04Check database service status
MCP support
The MCP server exposes SkySQL instance management, SQL execution, and service monitoring capabilities to AI agents and compatible clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMESkySQL MCP Server
This package contains everything needed to set up the SkySQL/MariaDB Cloud MCP (Model Context Protocol) server, which provides a powerful interface for managing SkySQL MariaDB database instances and interacting with AI Agents.
Features
- Launch and manage serverless MariaDB database instances
- Interact with AI-powered database agents
- Execute SQL queries directly on SkySQL (MySQL/MariaDB) instances
- Manage database credentials and IP allowlists
- List and monitor database services
Installation
Prerequisites
- Python 3.10 or higher
- A SkySQL/MariaDB Cloud API key
Option 1: Run locally
Installation steps
-
Clone the repository:
git clone [email protected]:skysqlinc/skysql-mcp.git cd skysql-mcp -
Run the installation script:
chmod +x install.sh ./install.sh -
Create a
.envfile in the root directory of the cloned git repository with your SkySQL API key. Obtain API key by signing up for free on SkySQL.SKYSQL_API_KEY=<your_skysql_api_key_here> -
Start the MCP server (HTTP mode):
chmod +x launch.sh ./launch.shThe server will start on
http://localhost:8000/mcpby default. -
Configure your IDE:
Cursor
Add the following to your Cursor MCP config (~/.cursor/mcp.json or .cursor/mcp.json in your project):
{
"mcpServers": {
"skysql-mcp-server": {
"url": "http://localhost:8000/mcp",
"headers": {
"X-API-Key": "<your-skysql-api-key>"
}
}
}
}
The
X-API-Keyheader is sent with each request, allowing per-user API keys when the server is hosted remotely.
Windsurf
Add the following to your Windsurf MCP config (~/.codeium/windsurf/mcp_config.json):
{
"mcpServers": {
"skysql-mcp-server": {
"serverUrl": "http://localhost:8000/mcp"
}
}
}
Note: Windsurf uses
serverUrl(noturl) and cannot send request headers. Start the server in single-tenant mode so it falls back to the API key in your environment:SKYSQL_SINGLE_TENANT=true ./launch.shWith
SKYSQL_API_KEYset in.env(step 3). WithoutSKYSQL_SINGLE_TENANT, the server requires every HTTP caller to supply its ownX-API-Keyheader and will reject requests that don't — deliberately, so a shared deployment can never serve requests using the operator's key.
Claude
Add the server as a custom connector (Settings > Connectors > Add custom connector), then supply your API key under Request headers:
| Field | Value |
|---|---|
| URL | your deployed server URL, ending in /mcp |
| Header name | x-api-key |
| Header value | your SkySQL API key, with no prefix |
| Required | yes |
Generate the key at app.skysql.com/user-profile/api-keys. Enter it exactly as-is — Claude sends the value verbatim and does not add a scheme or prefix.
Claude requires a publicly reachable HTTPS URL, so
http://localhost:8000/mcpwill not work here; deploy the server first. Request header authentication is currently in beta and may need to be enabled for your organization.
- (Optional) Test the server interactively with MCP CLI:
npx @wong2/mcp-cli uv run python src/mcp-server/server.py
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.