Loadster

Loadster MCP

Loadster is a cloud load testing and monitoring platform. Its built-in Model Context Protocol (MCP) server lets AI agents like Claude, ChatGPT, Codex, Cursor, and VS Code write and play load test scripts, build load test scenarios, set up monitors, and analyze results in your Loadster account.

This repository is the public home for connecting to that server: setup snippets for each client, the Claude Code plugin, and the metadata behind Loadster's listings in MCP directories. The server itself is hosted by Loadster at https://api.loadster.com/mcp, and its source is not published here. Loadster is also an official plugin in the ChatGPT and Codex plugin directory.

The maintained, full-length guide is the AI Assistants & MCP chapter of the Loadster manual. This README is the short version.

The Loadster MCP endpoint

OAuth is the easiest way to connect. Clients that support MCP OAuth send you to Loadster to approve the connection in your browser, and you can review or revoke connected agents on the API & MCP page in your Loadster settings.

Personal access tokens are for clients that can't do OAuth, and for CI jobs and scripted agents. The same kind of token also works for calling the Loadster REST API directly. Create one in the Loadster dashboard under Settings → API & MCP → Personal Access Tokens, copy it right away (it's only shown once), and send it as Authorization: Bearer YOUR_TOKEN. A token acts as you within the team where you created it, so treat it like a password.

Connecting Claude Code to Loadster

The quickest way is the plugin from this repository, which adds the Loadster MCP server plus skills for a sensible load testing workflow: setup to connect, setup-script for a first script, setup-scenario for a first load test scenario, setup-monitor for a first synthetic monitor, load-test for a full test, and results for reading what happened.

/plugin marketplace add loadster/loadster-mcp
/plugin install loadster@loadster

Then run /mcp, pick loadster, and approve the OAuth connection in your browser. Ask Claude something like "List my Loadster projects" to confirm it can reach your account.

Without the plugin, add the server directly and Claude Code will walk you through OAuth:

claude mcp add --transport http loadster https://api.loadster.com/mcp

Or with a personal access token, for headless use:

claude mcp add --transport http loadster https://api.loadster.com/mcp --header "Authorization: Bearer YOUR_TOKEN"

The equivalent project-level .mcp.json:

{
  "mcpServers": {
    "loadster": {
      "type": "http",
      "url": "https://api.loadster.com/mcp"
    }
  }
}

Connecting Claude Desktop and claude.ai to Loadster

Claude Desktop and claude.ai connect to remote MCP servers as custom connectors, which use OAuth.

1. Open Settings → Connectors and choose Add custom connector.
2. Enter a name and the URL https://api.loadster.com/mcp.
3. Choose Connect and approve the Loadster OAuth connection when your browser opens.
4. In a conversation, open the tools menu and turn on the Loadster connector.

Connecting ChatGPT and Codex to Loadster

Loadster is an official plugin in the ChatGPT and Codex plugin directory, with the setup, load-test, and results skills. The new setup-script, setup-scenario, and setup-monitor skills reach it when the directory listing is updated.

• ChatGPT: open the Loadster plugin, choose Install plugin, then Connect and approve the Loadster OAuth connection. Start a conversation with @Loadster. On a Business or Enterprise workspace, an admin may need to make it available under Workspace settings → Plugins first.
• Codex: install Loadster from the Plugins tab in the Codex desktop app, or run /plugins in the Codex CLI, then start a new session.

The Codex IDE extension doesn't support plugins, so it connects through Codex's MCP configuration, which the desktop app and CLI share:

codex mcp add loadster --url https://api.loadster.com/mcp
codex mcp login loadster

Or with a personal access token in ~/.codex/config.toml:

[mcp_servers.loadster]
url = "https://api.loadster.com/mcp"
bearer_token_env_var = "LOADSTER_MCP_TOKEN"

If the plugin isn't available on your ChatGPT account, you can still add Loadster as a custom connection in Developer mode (Settings → Security and login). Open Plugins, add a connection with the URL https://api.loadster.com/mcp, then add it to a new conversation from the tools menu and approve the OAuth connection.

Connecting Cursor to Loadster

Or add it to .cursor/mcp.json in your project (or ~/.cursor/mcp.json for all projects) and approve the OAuth connection when Cursor first connects:

{
  "mcpServers": {
    "loadster": {
      "url": "https://api.loadster.com/mcp"
    }
  }
}

To use a personal access token instead, add "headers": { "Authorization": "Bearer ${env:LOADSTER_MCP_TOKEN}" } and set LOADSTER_MCP_TOKEN in the environment before starting Cursor.

Connecting VS Code to Loadster

Or run MCP: Add Server from the Command Palette, or add it to .vscode/mcp.json:

{
  "servers": {
    "loadster": {
      "type": "http",
      "url": "https://api.loadster.com/mcp"
    }
  }
}

To use a personal access token, declare a promptString input with "password": true and reference it in an Authorization header. The manual has the complete example.

Connecting other MCP clients to Loadster

Any client that supports remote servers over Streamable HTTP can connect the same way. For clients that only support local (stdio) servers, the mcp-remote bridge usually works. Leave out the --header arguments to have it run the OAuth flow instead of using a token:

{
  "mcpServers": {
    "loadster": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://api.loadster.com/mcp", "--header", "Authorization: Bearer YOUR_TOKEN"]
    }
  }
}

What an agent can do with Loadster

The server exposes most of the Loadster dashboard. Clients fetch the live tool list when they connect, so this table is a map of the surface rather than the source of truth. The MCP tool reference in the Loadster manual is generated from the tool definitions themselves, with each tool's parameters and whether it is a Read, Write, or Sensitive write.

Some actions are intentionally left to humans. An agent cannot launch or stop a full load test, enable a monitor, manage notification policies or maintenance windows, or administer your team, billing, or Fuel. It gets everything ready and hands off so you push the launch button.

Every tool carries MCP annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), so clients that honor them can prompt before writes and deletes.

Safety practices for AI load testing

• The agent acts in your account. It edits the same scripts, scenarios, datasets, and monitors your team sees. Script changes create revisions you can restore, but it's still a good idea to review proposed changes and keep experiments in their own project.
• Only test what's yours. Point scripts only at systems you own or are authorized to test. Playing a script runs a single bot, but it's your responsibility either way.
• Scope your access. Use one token per agent or machine, name them clearly, and revoke any you no longer use. If an agent only needs to read, choose Read only instead of Full access when you approve the OAuth connection (the mcp:read scope), or check Read only when you create a token. It can then use only the tools that read, and can't change anything or play scripts. Review OAuth connections on the API & MCP page in your Loadster settings. See How Your Assistant Authenticates.

Support

• Setup help and questions: help@loadster.com
• Security issues: see SECURITY.md
• Problems with the contents of this repository (the README, plugin, or directory metadata): open an issue here

What's in this repository

License

The contents of this repository are released under the MIT License. The Loadster service itself is governed by Loadster's terms of service.