Load testing and monitoring: write and play scripts, build scenarios, and analyze results.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
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.
| 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 β AI Agents β 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.
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:
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:
Or with an MCP token, for headless use:
The equivalent project-level .mcp.json:
Claude Desktop and claude.ai connect to remote MCP servers as custom connectors, which use OAuth.
https://api.loadster.com/mcp.ChatGPT on the web connects through plugins created in Developer mode (Settings β 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:
Or with an MCP token in ~/.codex/config.toml:
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:
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.
Or run MCP: Add Server from the Command Palette, or add it to .vscode/mcp.json:
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.
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:
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.
| 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 |
The contents of this repository are released under the MIT License. The Loadster service itself is governed by Loadster's terms of service.
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