Loadster

com.loadster由 loadster.com 发布官方发布者v2.0.1更新于 Oct 31, 2026

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

已验证Streamable HTTP可网页运行开发者工具安全与监控

概览

AI 生成的概览

Loadster 托管的 MCP 服务器,让 AI 助手在你的 Loadster 账户中编写负载测试脚本、搭建测试场景、设置监控并分析结果。

可以做什么
  • 列出和创建项目,并读取 Loadster 文档、脚本 API、示例与命令结构定义
  • 创建、更新、复制、删除、导入、校验和试运行脚本,并管理版本、资源与截图
  • 管理数据集及其数据行
  • 创建和更新场景,并列出可用引擎
  • 启动、停止和查看负载测试,读取报告、URL 耗时与备注
  • 创建、启用、停用和删除监控,查看监控周期、事件与汇总
适用场景
适合已经在 Loadster 上做负载测试或合成监控的团队,希望助手代为起草脚本、组装场景、设置监控或解读测试与监控结果,而不必频繁切换仪表盘。
运行要求
使用 Loadster API 主机上的远程 Streamable HTTP 端点,无需本地安装包。需要 Loadster 账户和团队。认证方式为浏览器中的 OAuth 2.1,或使用个人访问令牌以 Authorization Bearer 请求头发送(部分客户端通过 LOADSTER_MCP_TOKEN 环境变量提供)。不支持远程服务器的客户端需要 mcp-remote 桥接。
安装前请注意
助手以你的身份在团队内操作,会修改团队共享的脚本、场景、数据集和监控,可能执行删除或整表替换。启动负载测试和启用监控会产生真实流量并可能消耗 Fuel,仅在确需时授予 Read+Write+Execute。被测页面的内容可能夹带注入指令。建议每个助手单独使用一个令牌,授予最低权限,并及时撤销不用的连接。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Loadster,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.loadster%2Floadster-mcp/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "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.

来源:README.md,提交 c448f08

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

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

评分

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