Keploy

io.github.keploy由 GitHub 帳號 keploy 發布v1.0.0更新於 Nov 2, 2026

End-to-end API testing — generate and run tests from OpenAPI, curl, Postman, or real user traffic.

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

Keploy 的遠端 MCP 端點，可從 OpenAPI、curl、Postman 或真實流量產生並執行端對端 API 測試。

可以做什麼
  • 依 OpenAPI 規格、curl 指令、Postman 集合或真實使用者流量產生 API 測試
  • 把錄製的 API 與整合流程連同資料 mock 一起回放成測試
  • 透過 AI 擴充 API 覆蓋率：探測邊界值、缺少欄位、型別錯誤與順序錯亂的呼叫
  • 錄製並回放資料庫、訊息佇列與外部 API 互動，不必重新建置基礎設施即可執行測試
  • 彙整 API、整合、單元與端對端覆蓋率報告
適用情境
適合想讓助理為現有服務建立或擴充自動化 API 與整合測試套件的情況，尤其是已有介面規格或流量錄製、希望不寫測試程式碼就能涵蓋 schema 與業務流程時。
執行需求
透過 streamable HTTP 存取的遠端 MCP 端點，需要 OAuth 驗證。需要 Keploy API 金鑰，以 Bearer 權杖形式放在 Authorization 標頭中，金鑰於 Keploy 帳號設定中產生。需要能連線至 Keploy 服務的網路。
安裝前請注意
Authorization 標頭會攜帶 Keploy API 金鑰，應視為機密並避免出現在共用日誌中；該金鑰產生後僅顯示一次。測試產生與覆蓋率分析在 Keploy 代管服務上進行，因此 API schema 與來自流量的資料會傳送給該第三方。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Keploy，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/io.github.keploy%2Fmcp/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": {
    "keploy": {
      "type": "http",
      "url": "https://api.keploy.io/client/v1/mcp"
    }
  }
}

README

[Keploy Logo]

[keploy%2Fkeploy | Trendshift]

⚡️ API tests faster than unit tests, from user traffic ⚡️

🌟 The must-have tool for developers in the AI-Gen era for 90% test coverage 🌟

[Slack] [LinkedIn] [YouTube] [X]

[Keploy CNCF Landscape] [GitHub Stars] [Help us reach 20k stars!]

Keploy is a developer‑centric API and integration testing tool that auto‑generates tests and data‑mocks faster than unit tests.

It records API calls, database queries, and streaming events — then replays them as tests. Under the hood, Keploy uses eBPF to capture traffic at the network layer, but for you it’s completely code‑less and language‑agnostic.

[Convert API calls to API tests test cases and Data Mocks using AI]

🐰 Fun fact: Keploy uses itself for testing! Check out our swanky coverage badge: [Coverage Status]  

Key Highlights

🎯 No code changes

Just run your app with keploy record. Real API + integration flows are automatically captured as tests and mocks. (Keploy uses eBPF under the hood to capture traffic, so you don’t need to add any SDKs or modify code.)

📹 Record and Replay complex Flows

Keploy can record and replay complex, distributed API flows as mocks and stubs. It's like having a very light-weight time machine for your tests—saving you tons of time!

👉 Read the docs on record-replay

[Convert API calls to test cases]

🐇 Complete Infra‑Virtualization (beyond HTTP mocks)

Unlike tools that only mock HTTP endpoints, Keploy records databases (Postgres, MySQL, MongoDB), streaming/queues (Kafka, RabbitMQ), external APIs, and more.

It replays them deterministically so you can run tests without re‑provisioning infra.

👉 Read the docs on infra virtualisation

[Convert API calls to test cases]

🧪 Combined Test Coverage

If you’re a developer, you probably care about statement and branch coverage — Keploy calculates that for you.

If you’re a QA, you focus more on API schema and business use‑case coverage — Keploy calculates that too. This way coverage isn’t subjective anymore.

👉 Read the docs on coverage

[ai test gen for api statement schema and branch coverage]

🤖 Expand API Coverage using AI

Keploy uses existing recordings, Swagger/OpenAPI Schema to find: boundary values, missing/extra fields, wrong types, out‑of‑order sequences, retries/timeouts.

This helps expand API Schema, Statement, and Branch Coverage.

👉 Read the docs on coverage

[ai test gen for api statement schema and branch coverage]

Other Capabilities

  • 🌐 CI/CD Integration: Run tests with mocks anywhere you like—locally on the CLI, in your CI pipeline (Jenkins, Github Actions..) , or even across a Kubernetes cluster. Read more

  • 🎭 Multi-Purpose Mocks: You can also use Keploy-generated Mocks, as server Tests!

  • 📊 Reporting: Unified reports for API, integration, unit, and e2e coverage with insights directly in your CI or PRs.

  • 🖥️ Console: A developer-friendly console to view, manage, and debug recorded tests and mocks.

  • ⏱️ Time Freezing: Deterministically replay tests by freezing system time during execution. Read more

  • 📚 Mock Registry: Centralized registry to manage, reuse, and version mocks across teams and environments. Read more

Quick Start

1. Install Keploy Agent

bash
source /dev/stdin <<<"$(curl -fsSL https://keploy.io/install.sh || echo 'echo Keploy installer download failed >&2; return 1')"

2. Record Test Cases

Start your app under Keploy to convert real API calls into tests and mocks.

bash
keploy record -c "CMD_TO_RUN_APP"

Example for Python:

bash
keploy record -c "python main.py"

3. Run Tests

Run tests offline without external dependencies.

bash
keploy test -c "CMD_TO_RUN_APP" --delay 10

Resources

- 📘 Installation

- 🏁 QuickStarts

Languages & Frameworks (Any stack)

Because Keploy intercepts at the network layer (eBPF), it works with any language, framework, or runtime—no SDK required.

Note: Some of the dependencies are not open-source by nature because their protocols and parsings are not open-sourced. It's not supported in Keploy enterprise.

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Questions?

Book a Live Demo / Enterprise Support

Want a guided walkthrough, dedicated support, or help planning enterprise rollout?

[圖片]   [圖片]

Prefer a calendar invite? Mention your availability in the email—we’ll send a calendar invite right away.

Documentation & Community

Contribute & Collaborate

Whether you're new or experienced, your input matters. Help us improve Keploy by contributing code, reporting issues, or sharing feedback.

Together, let's build better testing tools for modern applications.

來源：README.md，提交 558559c

工具

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版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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