Loadster

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.

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

The Loadster MCP endpoint

URL	https://api.loadster.com/mcp
Transport	Streamable HTTP
Authentication	OAuth 2.1 (preferred), or an MCP token in an Authorization: Bearer header
Registry name	com.loadster/loadster-mcp

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 AI Agents page in your Loadster settings.

MCP tokens are for clients that can't do OAuth, and for CI jobs and scripted agents. Create one in the Loadster dashboard under Settings → AI Agents → MCP 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 a few skills that encode a sensible load testing workflow:

/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 an MCP 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

ChatGPT on the web connects through plugins created 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.

Codex in the ChatGPT desktop app, the Codex CLI, and the Codex IDE extension share one configuration:

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

Or with an MCP token in ~/.codex/config.toml:

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

Connecting Cursor to Loadster

Install in Cursor

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 an MCP 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

Install in VS Code Install in VS Code Insiders

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 an MCP 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.

Group	Tools
Projects and documentation	list_projects, get_documentation, get_scripting_api, get_example, list_command_types, get_command_schema, get_variable_schema
Scripts	list_scripts, get_script, create_script, update_script, duplicate_script, delete_script, import_script, validate_script, play_script, get_play_status, stop_script, get_step_detail, get_screenshot, list_script_revisions, get_script_revision, restore_script_revision, list_script_assets, get_script_asset, put_script_asset, delete_script_asset
Datasets	list_datasets, get_dataset, create_dataset, update_dataset, append_dataset_rows, delete_dataset
Scenarios and engines	list_scenarios, get_scenario, create_scenario, update_scenario, delete_scenario, list_engines
Load test reports	list_load_tests, get_load_test_report, update_load_test_notes
Monitoring	list_monitoring_locations, list_monitors, get_monitor, create_monitor, update_monitor, disable_monitor, delete_monitor, list_monitor_cycles, get_monitor_cycle_detail, get_monitoring_summary, list_incidents, get_incident
Feedback	submit_feedback

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. Review OAuth connections on the AI Agents page.

Support

• Setup help and questions: [email protected]
• 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

Path	Purpose
server.json	Loadster's entry in the official MCP Registry
glama.json	Maintainer metadata for the Glama listing
.claude-plugin/, .mcp.json, skills/	The Claude Code plugin and its marketplace manifest
.github/workflows/	Validation on every push, and registry publishing on release

License

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