Maxoperf

com.maxoperf由 maxoperf.com 發布官方發布者v1.0.0更新於 Oct 24, 2026

Load & browser performance testing — drive MaxoPerf from your AI agent with your API key.

已驗證Streamable HTTP可網頁執行雲端與基礎設施開發者工具資料與分析

概覽

AI 產生的概覽

託管的 MaxoPerf MCP 伺服器,讓 AI 助理建立並執行負載與瀏覽器效能測試、讀取結果並診斷失敗原因。

可以做什麼
管理帳戶脈絡:解析帳戶、列出工作區與專案、設定使用中的工作區、建立專案與測試,並查看測試執行歷史與檔案(上傳、列出、下載)。啟動與控制執行:在託管雲端執行器上啟動負載或瀏覽器執行、輪詢狀態、列出與重跑執行、增加執行器、取消執行。讀取結果:KPI 概覽、時間序列指標和分組錯誤列。診斷問題:執行摘要、取樣錯誤請求內容、引擎日誌、執行器健康狀態和確定性異常偵測。透過通用 API 呼叫、OpenAPI 文件與端點搜尋存取其他平台端點。
適用情境
當你希望助理在 MaxoPerf 雲端執行器上規劃、啟動並觀察效能或負載測試,再用自然語言解釋結果或失敗原因,而不必離開聊天用戶端時使用。
執行需求
遠端託管端點,無需安裝。需要 MaxoPerf 帳戶和在主控台 Settings > API keys 建立的 API 金鑰,以 bearer 權杖形式放在 Authorization 標頭中(例如透過 MAXOPERF_API_KEY 變數)。需要能存取該託管端點的網路。
安裝前請注意
API 金鑰是每次呼叫都會傳送的機密,請勿放入共用設定,外洩後立即撤銷。寫入類工具會建立專案與測試、上傳檔案、啟動、重跑、擴充和取消執行,可能消耗付費雲端執行器資源。唯讀模式標頭會隱藏寫入工具,但這只是用戶端選擇,並非保證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Maxoperf,將其新增到工作區。
  2. 連接 Authorization token 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.maxoperf%2Fmaxoperf/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。

{
  "mcpServers": {
    "maxoperf": {
      "type": "http",
      "url": "https://app.maxoperf.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

⚡ MaxoPerf MCP Server

Drive the entire MaxoPerf platform from any AI agent — with your API key.

A remote, hosted Model Context Protocol server that turns Claude, Cursor, Codex, VS Code Copilot, and ChatGPT into a full performance-testing operator. Create tests, launch load runs on managed cloud runners, read results, and get root-cause analysis — all in natural language, all authenticated with your own key.

[MCP] [Claude] [Cursor] [ChatGPT]

https://app.maxoperf.com/mcp

Configuration

It's a remote, hosted server — nothing to install or run. Add this to your MCP client config and set MAXOPERF_API_KEY (create one in the console → Settings → API keys):

json
{  "mcpServers": {    "maxoperf": {      "type": "http",      "url": "https://app.maxoperf.com/mcp",      "headers": {        "Authorization": "Bearer ${MAXOPERF_API_KEY}"      }    }  }}

Your key is validated on every call by the real platform (auth, tenancy, OpenFGA, audit) — the server stores nothing and adds no new trust boundary. Revoke the key, access dies instantly. Send the header X-MaxoPerf-MCP-Mode: read-only for a look-but-don't-touch session (write tools hidden).

Install (pick your client)

Claude Code — the plugin bundles the server and the agent skill:

/plugin marketplace add MaxoPerf/mcp/plugin install maxoperf

Or add just the connector:

claude mcp add --transport http maxoperf https://app.maxoperf.com/mcp \  --header "Authorization: Bearer ${MAXOPERF_API_KEY}"

Cursor · VS Code / Copilot · Codex · ChatGPT · Claude Desktop — one-click deeplinks and copy-paste config in packaging/. All use the same mcpServers block above.


Tools

29 curated tools. Reads default to response_format: "concise" (pass "detailed" for the full payload); write tools require a non-read-only session, and cancel_run is hidden in read-only mode.

Context & tenancy

  • whoami — Resolve the account + default workspace behind your API key
  • list_workspaces — List workspaces visible to the account
  • set_active_workspace — Set the active workspace for the session
  • list_projects — List projects (with edit/delete permissions)
  • create_project — Create a project

Tests

  • list_tests — List tests (filter by project / workspace / type)
  • get_test — Get one test + its validation summary
  • create_test — Create a test shell (choose the engine/executor)
  • get_test_overview — Run-history overview for a test

Test files

  • upload_test_file — Upload a script/data file in one call (real 3-step presigned flow)
  • list_test_files — List a test's files + upload state
  • download_test_file — Get a short-lived download URL for a file

Runs

  • start_run — Launch a load/browser run on managed cloud runners (idempotent)
  • get_run_status — Poll lifecycle status (queued → running → passed/failed/cancelled)
  • list_runs — Paginated run history with filters
  • cancel_run — Cancel a run (destructive; hidden in read-only)
  • rerun_run — Re-run from a snapshot or the current test
  • add_runners — Scale a live run up at existing locations

Results

  • get_run_results — KPI overview: throughput, latency percentiles, error rate
  • query_run_metrics — Time-series metrics (latency / throughput / errors / load / health)
  • get_run_errors — Grouped error rows (message / count / code)

Diagnostics — root-cause & anomaly detection

  • get_run_summary — Executive summary + which failure criteria tripped
  • get_run_error_bodies — Sampled error request/response bodies + status codes
  • get_run_logs — Error-level engine/system log lines
  • get_runner_health — Runner CPU/mem trend + targetVus vs peakAchievedVus (vuShortfallPct)
  • detect_run_anomalies — Deterministic robust-outlier scan (median/MAD); terminal-gated, low false-positive

Escape hatch & discovery

  • call_platform_api — Reach any public /v1/* endpoint (secrets, environments, schedules, BYOC); admin/internal deny-listed, SSRF-safe
  • get_openapi — The public OpenAPI document
  • search_endpoints — Keyword search over the API to find the right endpoint

Prompts

Text recipes that encode the correct tool sequence — great for chat-only clients that can't read a repo:

  • run-baseline-load-test — Start a baseline run and watch it to completion
  • diagnose-latency-regression — Compare p95 across two runs
  • summarize-run — Plain-language summary of one run
  • plan-and-build-test — Turn a goal into project → test → upload → run
  • choose-executor — Recommend an engine (k6 / JMeter / Playwright / Selenium)
  • scan-endpoints-for-hotspots — Rank likely hotspots from an OpenAPI spec or pasted list
  • setup-secrets-and-envs — Wire workspace secrets + multi-env before a run
  • diagnose-run-failure — Ranked root cause for a failed run
  • explain-run-anomalies — Explain each detected outlier

Resources

  • maxoperf://openapi — The public OpenAPI spec
  • maxoperf://run/{id} — A run report summary

Try it

  • "Load test https://api.example.com/checkout with 500 users for 5 minutes and fail it if p95 goes over 800ms."
  • "Scan my repo for the endpoints most worth load-testing, then build and run a test for the riskiest one."
  • "Why did run run-0000000001 fail? Check the errors, the logs, and whether the runners actually reached the target load."

Pair it with the brain

The MCP server is the hands. The bundled MaxoPerf agent skill (npx @maxoperf/agent-skill install, included in the Claude plugin, or in agent-skill/ here) is the brain — it reads your code, finds the hotspots, builds and runs the test, and diagnoses why it broke, driving these tools automatically.

What's in this repo

PathWhat
.claude-plugin/Claude Code plugin (bundles the MCP connector + the skill)
agent-skill/A copy of the maxoperf agent skill (canonical home: MaxoPerf/agent-skill)
packaging/MCP Registry server.json, .mcpb, VS Code / Cursor deeplinks, Codex / ChatGPT setup
LAUNCHGUIDE.mdMCP directory listing metadata

Get started → · Agent skill → · Docs →

Read-only mirror of the MaxoPerf monorepo. File issues at maxoperf.com.

來源:README.md,提交 406f884

工具

0
該伺服器需要 API 金鑰等憑證,因此 SourceWeft 無法在沒有憑證的情況下讀取其工具,也未收錄。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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