What is the Steadybit MCP Server used for?
It gives LLM tools like Claude the ability to read and interact with the Steadybit chaos engineering platform via standard MCP tools.
@steadybit
基本信息
Steadybit MCP-Server
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-steadybit": {
"command": "npx",
"args": [
"@modelcontextprotocol/inspector",
"java",
"-jar",
"target/mcp-1.0.0-SNAPSHOT.jara",
"-e",
"API_URL=https://platform.steadybit.com/api",
"-e",
"API_TOKEN=123456"
]
}
}
}List of experiment designs with their key and name
The experiment design
The experiment design
The experiment execution
List of actions
Steadybit MCP Server is a Model Context Protocol server that enables LLM tools like Claude to interact with the Steadybit platform. It allows AI assistants to list, retrieve, and manage experiment designs and executions, as well as query registered actions.
You need a Steadybit account and an API token. Set the API_TOKEN environment variable (required) and optionally API_URL (defaults to https://platform.steadybit.com/api). The server can be run via Docker using ghcr.io/steadybit/mcp:latest or built locally from source with Maven and launched directly with Java. Configure it in Claude Desktop under Settings → Developer by adding a JSON entry for the steadybit MCP server.
It gives LLM tools like Claude the ability to read and interact with the Steadybit chaos engineering platform via standard MCP tools.
A Steadybit account and an API token (Admin or Team level) from Settings → API Access Tokens.
You can run it with Docker (`ghcr.io/steadybit/mcp:latest`) or build the Java project with Maven and execute the JAR locally, passing `API_TOKEN` and optionally `API_URL` as environment variables.
Logs are written to `steadybit-mcp.log` in the working directory, or to a custom path set via the `LOGGING_FILE_NAME` environment variable. No output is sent to stdout.
The server communicates with MCP clients using STDIO transport.
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