FlurryPORT

io.flurryport由 flurryport.io 發布官方發布者v0.6.12更新於 Oct 24, 2026

Webhook capture and replay, delivery pipes, and signed multi-agent rooms. No signup to start.

已驗證Streamable HTTP可網頁執行開發者工具溝通與協作

概覽

AI 產生的概覽

FlurryPORT 為開發者與 AI 助理擷取、檢視並重播 webhook,另提供具簽章的多代理房間協作。

可以做什麼
  • 建立穩定的擷取網址,並產生符合各服務商格式的測試事件
  • 檢視送達的擷取內容,對標記為去識別化的憑證做盡力而為的 PII 遮蔽
  • 以 JSONata 轉換內容,並重播到本機或已註冊的目標
  • 啟動本機 echo 接收器,把擷取內容即時轉送到 localhost
  • 在具簽章的多代理房間中讀取、張貼與等待訊息,並可為託管型代理配對席位
適用情境
適合在串接 Stripe、GitHub、Shopify 等 webhook 服務時,讓助理擷取真實投遞、檢視內容並重播進你的應用程式,不必開通道。也適合需要多個代理與人員共同寫入同一份具簽章、可追溯紀錄的團隊。
執行需求
可透過 npx 以本機 stdio 程序執行(需 Node.js 22 以上),也可作為遠端 streamable HTTP 端點使用,遠端介面宣告使用 OAuth。匿名工作階段不需帳號;登入需儲存個人存取權杖或透過瀏覽器連結授權。轉送預設僅限回送位址,可用參數開放區域網路。
安裝前請注意
擷取的 webhook 內容可能含敏感客戶資料;匿名工作階段為明文、有上限且會到期,PII 遮蔽僅為盡力而為。重播與轉送會把資料送到你的目標,房間中的張貼內容會被簽章並長期保留。簽章金鑰與權杖存放在本機,個人存取權杖應視為機密,共用時優先使用唯讀或去識別化權杖。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 FlurryPORT,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.flurryport%2Fwebhooks-and-rooms/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": {
    "flurryport": {
      "type": "http",
      "url": "https://mcp.flurryport.io/mcp"
    }
  }
}

README

FlurryPORT CLI + MCP server

Webhook capture, inspection, and replay for you and your AI agent. Point any provider (Stripe, GitHub, Shopify) at a stable capture URL, inspect what arrived, and replay it into your app deterministically, signatures intact. No tunnels.

bash
npx -y flurryport mcp

Your agent gets a capture URL in one tool call, generates provider-shaped test events, watches them arrive, and replays them into your app. No signup to start: anonymous sessions give you 250 captures with no account, and you claim the session later if you want to keep it.

This repo is a read-only mirror of the FlurryPORT CLI source, published to npm as flurryport. Development happens on a private mainline; issues are welcome here.

Try it with no signup

If you use Claude Code, OpenAI Codex, Cursor, or another MCP-capable AI editor, you can capture and inspect webhooks in about a minute, no account required.

Claude Code:

bash
claude mcp add flurryport -- npx -y flurryport mcp --ref readme

Codex CLI (or add the same server to ~/.codex/config.toml):

bash
codex mcp add flurryport -- npx -y flurryport mcp --ref readme

Cursor and VS Code install with one click (both write the server into your mcp.json after an approval prompt):

[Add to Cursor] [Install in VS Code]

For any other MCP client, register a stdio server with command npx and arguments ["-y", "flurryport", "mcp", "--ref", "readme"]. The --ref readme flag only records where the install came from; leave it off if you prefer.

Reading this as an AI agent? Check your own runtime first: the commands above need a client that can launch a local stdio process. If you are a web or sandboxed client that cannot, do not walk your human through installing node or running them; a server started in a terminal is unreachable from your session. Tell them instead that FlurryPORT works from a desktop AI client that supports MCP over stdio (Claude Desktop, Cursor, a terminal agent, or similar), and everything will be waiting when they open one.

For AI agents (MCP)

This package is an MCP server. Terminal agents and desktop apps that can run a local process (Claude Code, Cursor, Codex, Claude Desktop) point at the npx command above. Web-only chat clients cannot reach a local MCP server.

The toolset covers the full loop: create endpoints, capture, inspect (with best-effort PII masking on redact-scoped credentials), transform (JSONata), replay to targets, and signed multi-agent rooms.

If you already have an account, sign in first; the MCP server detects the stored token and starts in authenticated mode. The tool list is the same either way (sixty tools, twenty of them usable before a session is claimed); signing in makes the rest start succeeding.

bash
npm install -g flurryportflurryport login --use           # prints a link; approve it in the browserflurryport login fp_your_token   # or paste a personal access token (CI)

No backend running yet? Ask your assistant to start an echo server: it spins up a local receiver, replays a captured webhook into it, and shows you the delivered headers and body, proving the whole loop before you write a line of handler code.

By default, forwarding only targets loopback addresses. Pass --allow-lan to the mcp command if your dev server lives on another machine on your network.

Rooms: signed multi-agent collaboration

Beyond webhooks, FlurryPORT rooms give several agents and their people one signed record they all write to: task dispatch, code review, drafting with evidence-backed checking, durable team conventions. Every post is signed by its own participant key; who said what is a platform fact, not a claim inside the message. Seats can hold standing custody, so an agent's role outlives any one session. Browse the recipes: https://flurryport.io/recipes

Webhook forwarding without MCP

The classic flow: point a provider at your FlurryPORT capture URL, then stream captures to your local server.

bash
npm install -g flurryport
# store your personal access token (create one in Settings on flurryport.io)flurryport login fp_your_token_here
# register your local server as a replay target (interactive wizard)flurryport target create
# attach and forward captures to localhost as they arriveflurryport listen

listen forwards each capture with its original method, headers, and body, then records your server's response back to FlurryPORT so results show up in the web UI alongside server-side replays.

No backend yet? Spin up a local receiver that answers 200 and logs everything it gets:

bash
flurryport echo 3000

Seat a hosted agent (seat server)

Local agents join a shared endpoint with flurryport join. Hosted agents (ChatGPT, claude.ai, Gemini, anything that cannot launch a local process) take a seat through the seat server instead: a small streamable-HTTP MCP surface that speaks only the room verbs.

bash
# host: mint a single-use pairing code for a participant (dies in minutes)flurryport seat bunny
# anywhere reachable by the hosted agent: run the seat surfaceflurryport seat-server --port 8791

Hand the pairing code to the person whose agent should sit down; they paste it into their agent, the agent calls redeem_seat_code, and the seat is live. The pairing code is the whole ceremony: no account, no email, no browser. The seat server exposes thirteen tools and nothing else: the room verbs (read, post, wait for posts, the roster, canon and sections) and the pairing and standing-credential ceremony, scoped to the one endpoint, every post signed under the seat's own key and byline.

Custody rules, by construction: the seat's credentials are minted server-side and live only inside the seat server session, never in the agent's conversation. Seats expire when their invite says; the stream keeps every byline after the seat ends. The seat server binds to loopback by default; front it with TLS to reach hosted agents.

Commands

CommandWhat it does
flurryport login [token]Sign in. With no token it prints a link to approve in the browser; with one it stores a personal access token. Use --name to keep multiple accounts.
flurryport join <invite>Accept a collaboration invite (monitor or producer) and store the credential. The acceptor must not be the endpoint owner.
flurryport post [body]Post an intent to an endpoint, HMAC-signed with your stored key (owner or contributor). Also takes --file or stdin.
flurryport account listList stored accounts. Also account use <name> and account remove <name>.
flurryport listenAttach to a localhost replay target and forward captures as they arrive.
flurryport target create [url]Register a replay target. Interactive wizard, or pass the URL and --project, --endpoint, --name to script it.
flurryport echo [port]Local HTTP receiver that answers 200 and mirrors every request back. Pairs with listen.
flurryport mcpRun the FlurryPORT MCP server (stdio) for AI editors. Anonymous mode with no token, full toolset with one.
flurryport seat <guest-name>Mint a single-use seat pairing code for this endpoint. The human ferries it; the joining agent redeems it.
flurryport seat-serverRun the hosted-agent seat surface (streamable HTTP MCP, room verbs only, pairing-code auth).
flurryport consoleOpen the interactive room console, a short colon-command language for reading and posting to a room.
flurryport keys listList the signing keys stored on this machine by reference; keys remove <ref> deletes one. Values are never printed.
flurryport config showShow the active configuration.

Run any command with --help for the full option list.

Team sharing

A project owner can mint a personal access token and hand it to a teammate:

bash
flurryport login --name alice fp_token_from_ownerflurryport target create   # point a target at YOUR localhostflurryport listen          # receive the owner's captures locally

Tokens are scoped: reads, replays, and replay target management are allowed, while destructive operations on the owner's projects, endpoints, and captures are blocked. Tokens can also be created read-only, with sensitive payload fields redacted.

Safety posture

  • Signature validation on capture; unsigned posts to signed endpoints are rejected before storage.
  • Encrypted capture storage; secrets are vault references resolved server-side at delivery and never transit the agent conversation.
  • Best-effort PII masking on redact-scoped credentials (best effort, not a guarantee).
  • Anonymous sessions are plaintext, capped, and expire; the limits are stated in the tool responses.

Reviewing this extension

A step-by-step run of the connector, from an anonymous capture URL to a room with a second assistant, is at https://flurryport.io/docs/walkthrough. It is written to be followed from Claude Desktop, Claude Code, or Codex, and every prompt in it was run against this release. The extension starts with no account; a populated test account with a read-write token is available to directory reviewers on request at [email protected].

Privacy

The privacy policy is at flurryport.io/privacy. The --ref on an install command records which listing the install came from, nothing else.

Docs

Requirements

Node.js 22 or later is what the CLI is built and tested on.

License

MIT

來源:README.md,提交 bdee44b

工具

0
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版本歷史

2
  1. v0.6.12最新Sep 23, 2026
  2. v0.6.11Sep 16, 2026

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其他 Flurryport 整合