Loadster

com.loadster由 loadster.com 發布官方發布者v2.0.1更新於 Oct 31, 2026

Load testing and synthetic monitoring platform: test with Playwright, Browser Bot, or Protocol Bots.

已驗證Streamable HTTP可網頁執行開發者工具安全與監控

概覽

AI 產生的概覽

Loadster 託管的 MCP 伺服器,讓 AI 助理在你的 Loadster 帳號中撰寫負載測試腳本、建立測試情境、設定監控並分析結果。

可以做什麼
  • 列出與建立專案,並讀取 Loadster 文件、腳本 API、範例與指令結構定義
  • 建立、更新、複製、刪除、匯入、驗證與試跑腳本,並管理版本、資源與截圖
  • 管理資料集及其資料列
  • 建立與更新情境,並列出可用引擎
  • 啟動、停止與查看負載測試,讀取報告、URL 耗時與備註
  • 建立、啟用、停用與刪除監控,查看監控週期、事件與彙總
適用情境
適合已在 Loadster 上進行負載測試或合成監控的團隊,希望助理代為草擬腳本、組裝情境、設定監控或解讀測試與監控結果,而不必頻繁切換儀表板。
執行需求
使用 Loadster API 主機上的遠端 Streamable HTTP 端點,無需本機套件。需要 Loadster 帳號與團隊。驗證方式為瀏覽器中的 OAuth 2.1,或使用個人存取權杖以 Authorization Bearer 標頭送出(部分用戶端透過 LOADSTER_MCP_TOKEN 環境變數提供)。不支援遠端伺服器的用戶端需要 mcp-remote 橋接。
安裝前請注意
助理會以你的身分在團隊內操作,修改團隊共用的腳本、情境、資料集與監控,可能執行刪除或整份清單取代。啟動負載測試與啟用監控會產生真實流量並可能消耗 Fuel,僅在確有必要時授予 Read+Write+Execute。受測頁面的內容可能夾帶注入指令。建議每個助理各用一個權杖,授予最低權限,並及時撤銷不再使用的連線。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Loadster,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.loadster%2Floadster-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

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

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

URLhttps://api.loadster.com/mcp
TransportStreamable HTTP
AuthenticationOAuth 2.1 (preferred), or a personal access token in an Authorization: Bearer header
Registry namecom.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:

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

Or with a personal access token, for headless use:

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

The equivalent project-level .mcp.json:

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:

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

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

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

[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:

json
{  "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

[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:

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:

json
{  "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.

GroupTools
Projects and documentationlist_projects, create_project, get_documentation, get_scripting_api, get_example, list_command_types, get_command_schema, get_variable_schema
Scriptslist_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
Datasetslist_datasets, get_dataset, create_dataset, update_dataset, append_dataset_rows, delete_dataset
Scenarios and engineslist_scenarios, get_scenario, create_scenario, update_scenario, delete_scenario, list_engines
Load tests and reportslaunch_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
Monitoringlist_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
Feedbacksubmit_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: [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

PathPurpose
server.jsonLoadster's entry in the official MCP Registry
glama.jsonMaintainer 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.

來源:README.md,提交 c448f08

工具

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版本歷史

5
  1. v2.0.1最新Oct 31, 2026
  2. v1.6.0Oct 29, 2026
  3. v1.4.0Oct 22, 2026
  4. v1.3.0Oct 20, 2026
  5. v1.2.0Sep 16, 2026

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