FlurryPORT

io.flurryport由 flurryport.io 发布官方发布者v0.6.12更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行开发者工具沟通与协作

概览

AI 生成的概览

FlurryPORT 为开发者和 AI 助手捕获、检查并重放 webhook,并提供带签名的多智能体房间协作。

可以做什么
  • 创建稳定的捕获地址,并生成符合各服务商格式的测试事件
  • 检查到达的捕获内容,对标记为脱敏的凭据做尽力而为的 PII 遮蔽
  • 用 JSONata 转换载荷,并重放到本地或已注册的目标
  • 启动本地 echo 接收器,把捕获实时转发到 localhost
  • 在带签名的多智能体房间中读取、发布和等待消息,并可为托管型智能体配对席位
适用场景
适合在对接 Stripe、GitHub、Shopify 等 webhook 服务时,让助手捕获真实投递、检查内容并重放进你的应用,无需内网穿透。也适合需要多个智能体与人共同写入同一份带签名、可追溯记录的团队。
运行要求
可通过 npx 作为本地 stdio 进程运行(需 Node.js 22 或更高版本),也可作为远程 streamable HTTP 端点使用,远程接口声明使用 OAuth。匿名会话无需账号;登录需存储个人访问令牌或通过浏览器链接授权。转发默认仅限回环地址,可用参数允许局域网。
安装前请注意
捕获的 webhook 载荷可能含敏感客户数据;匿名会话为明文、有配额且会过期,PII 遮蔽仅为尽力而为。重放与转发会把数据发送到你的目标,房间中的发布内容会被签名并长期保留。签名密钥与令牌保存在本机,个人访问令牌应视为机密,共享时优先使用只读或脱敏令牌。

安装

在 SourceWeft 中

  1. 打开 控制台中的 FlurryPORT,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/io.flurryport%2Fwebhooks-and-rooms/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": {
    "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

来源:README.md,提交 bdee44b

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

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

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