Server data from the Official MCP Registry
Load testing and synthetic monitoring platform: test with Playwright, Browser Bot, or Protocol Bots.
About
Load testing and synthetic monitoring platform: test with Playwright, Browser Bot, or Protocol Bots.
Remote endpoints: streamable-http: https://api.loadster.com/mcp
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Found in Source Code
Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"com-loadster-loadster-mcp": {
"url": "https://api.loadster.com/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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
| URL | https://api.loadster.com/mcp |
| Transport | Streamable HTTP |
| Authentication | OAuth 2.1 (preferred), or a personal access 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 API & MCP page in your Loadster settings. The approval page leads with the web address Loadster can verify for the app, so check that it's one you expect before you approve. You also choose an access level there: Read (selected to start with), Read+Write, or Read+Write+Execute. To change it later, revoke the connection and connect again. Changing or resetting your Loadster password disconnects every OAuth-connected agent, so reconnect each one afterward. Personal access tokens keep working.
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, choose its access level, 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.
- Open Settings → Connectors and choose Add custom connector.
- Enter a name and the URL
https://api.loadster.com/mcp. - Choose Connect and approve the Loadster OAuth connection when your browser opens.
- 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
/pluginsin 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, Sensitive Write, or Execute tool.
| Group | Tools |
|---|---|
| Projects and documentation | list_projects, create_project, 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 tests and reports | launch_load_test, stop_load_test, get_load_test_status, list_load_tests, get_load_test_report, get_load_test_url_timings, update_load_test_notes |
| Monitoring | list_monitoring_locations, list_monitors, get_monitor, create_monitor, update_monitor, enable_monitor, disable_monitor, delete_monitor, list_monitor_cycles, get_monitor_cycle_detail, get_monitoring_summary, list_incidents, get_incident |
| Feedback | submit_feedback |
Scripts, scenarios, datasets, and monitors can carry tags. The list tools report each item's tag names, and the
create and update tools take a tags list. Tags are shared across your team, so agents reuse the names you already
have and create a new tag only when you ask for one.
Updating a script, scenario, monitor, or dataset changes only the fields the agent sends and keeps the rest. A list
that's sent, such as a scenario's bot groups or a dataset's rows, replaces the stored list rather than merging into
it. The load test tools take loadTestId and scenario bot groups take engineId; the older names testId and
loadEngineId still work in 2.0 and will be removed in the next major version.
The tools an agent sees depend on the access level you grant. Read sees the tools that read, Read+Write
adds the tools that create, change, delete, and play scripts, and Read+Write+Execute adds launch_load_test,
stop_load_test, and enable_monitor. Launching a load test and enabling a monitor send real traffic and burn
Fuel unless your plan covers them, so the server tells the agent to get your go-ahead before either. Before a
launch the agent gives you your balance and, when the test would burn Fuel, the Fuel estimate range the dashboard
shows. A launch with no estimate runs on your plan and burns no Fuel, and one with an estimate runs entirely on
Fuel. If your plan can't run a test right now, the agent's launch is refused and you can launch it on Fuel from the
dashboard. Monitors are covered by a plan that includes monitoring up to its limits, and use Fuel beyond them. At
the other two levels the agent gets everything ready and hands off so you push the launch button in the dashboard.
Some actions are always left to humans. An agent cannot manage notification policies or maintenance windows, or administer your team, billing, or Fuel.
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.
- Pages under test can talk to your agent. Response bodies, page HTML, console output, logs, screenshots, and monitor messages come from the site you're testing, and anyone who can put text there can put instructions there. Loadster marks that content as untrusted data and tells agents not to follow instructions inside it, but agents can still be misled, so a read-only connection is safer when an agent only needs to analyze results.
- 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. Grant the lowest access level the agent needs. If it only needs to read, keep Read (selected to start with) when you approve the OAuth connection, or choose Read when you create a token. It can then use only the tools that read, and can't change anything or play scripts. Choose Read+Write+Execute only for an agent you want launching load tests or enabling monitors. 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
| 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, its marketplace manifest, and the setup, setup-script, setup-scenario, setup-monitor, load-test, and results skills |
.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.
Reviews
No reviews yet
Be the first to review this server!
More Developer Tools MCP Servers
Rea
Freeby Morluto · Developer Tools
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Paperclip
Freeby Paperclipai · Developer Tools
Trending hip-hop artist momentum scores across four cultural dimensions.
Fetch
Freeby Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
Git
Freeby Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
Toleno
Freeby Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
MCP Marketplace
Freeby mcp-marketplace · Developer Tools
Search and install MCP servers from inside your AI client.
