OP3 MCP Server

io.github.conorbronsdon由 GitHub 帳號 conorbronsdon 發布v0.2.0更新於 Oct 24, 2026

OP3 podcast analytics: downloads, geography, app share, episode breakdowns. Read-only.

已驗證STDIO僅桌面資料與分析媒體與設計

概覽

AI 產生的概覽

為助理提供唯讀的 OP3 播客分析:下載量趨勢、聽眾地理分布、應用程式占比與單集資料。

可以做什麼
將助理連接到 Open Podcast Prefix Project(OP3)分析 API。工具可用訂閱源 URL、播客 GUID 或節目 UUID 查詢節目,接著回傳每月與每週下載量、單集在 1/3/7/30 天及全部的下載量、熱門收聽應用程式、熱門聽眾國家,以及包含時間、國家、應用程式與裝置的原始下載事件時間序列。所有工具皆為唯讀。
適用情境
適合讓助理回答播客受眾相關問題:下載趨勢、聽眾所在地、使用的應用程式,以及各單集表現,尤其在託管平台 API 只提供下載量時更有價值。前提是該節目已透過 OP3 前綴分送下載。
執行需求
透過 npx 從 npm 套件 @conorbronsdon/op3-mcp 以 stdio 在本機執行,需要 Node.js 以及連線 OP3 API 的網路。需要 OP3 API 權杖,透過環境變數 OP3_API_TOKEN 提供;官方另發布一組共用預覽權杖,可用於公開節目。多數工具需要節目 UUID,可由訂閱源 URL 或播客 GUID 取得。
安裝前請注意
OP3_API_TOKEN 是憑證,應避免寫入共用設定檔。此伺服器為唯讀,無法變更任何內容。地理與國家資料由用戶端依原始下載紀錄統計,屬於取樣而非精確總量;熱門應用程式視窗固定為最近三個日曆月;資料僅從加入 OP3 前綴之後開始。速率限制未公開,請將 limit 與 max_records 保持在較小值。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 OP3 MCP Server,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

op3-mcp

Podcast analytics for AI agents through OP3: downloads over time, listener geography, apps, and per-episode breakdowns. Read-only.

[License: MIT] [npm version] [Node] [Podcast] [X]

[Demo: an agent calls the op3_show_downloads tool and gets monthly and weekly download counts back (sample data)]

An MCP server for OP3, the Open Podcast Prefix Project. It gives AI assistants podcast analytics that most hosting APIs do not expose: downloads over time, listener geography, the apps people listen in, and per-episode breakdowns.

Read-only by design. OP3 is an analytics service. This server only reads data. It cannot change anything, so it is safe to give an agent.

Why this exists. Most podcast hosts expose almost nothing through their API. Transistor's API, for example, returns download counts and not much else: no geography, no app share, no per-episode recency curve. OP3 has all of that, because it logs each download at the redirect. This server puts that data in front of an agent.

[op3-mcp MCP server]

What is OP3?

OP3 is a free, open analytics prefix for podcasts. You add https://op3.dev/e/ in front of your enclosure URLs, and OP3 logs each download before redirecting to your real audio file. It then reports downloads, geography, and app share. Stats pages are public; the API needs a token. See https://op3.dev for details.

If your feed does not use the OP3 prefix yet, OP3 has no data for it. See "Adding the OP3 prefix" below.

Tools

ToolWhat it returnsOP3 endpoint
op3_get_showShow UUID, title, podcast GUID, stats page URL, optional episode listGET /shows/{showUuidOrPodcastGuidOrFeedUrlBase64}
op3_show_downloadsMonthly downloads, weekly breakdown, weekly averageGET /queries/show-download-counts
op3_episode_downloadsPer-episode downloads at 1/3/7/30 days and all-timeGET /queries/episode-download-counts
op3_top_appsTop apps/players by download share, last 3 calendar monthsGET /queries/top-apps-for-show
op3_top_countriesTop listener countries or regions (computed from raw records)GET /downloads/show/{showUuid}
op3_downloads_timeseriesRaw download events over a date range (time, country, app, device)GET /downloads/show/{showUuid}

Most tools need a show UUID. Start with op3_get_show to turn a feed URL or podcast GUID into a UUID.

Every list tool takes a limit and defaults it low (10) to keep responses small. Agents pay tokens per response.

Setup

1. Get a token

  1. Go to https://op3.dev and sign in.
  2. Open your API token page and copy the token.
  3. For trying things out, OP3 also publishes a shared preview token, preview07ce, which works against public shows.

2. Find your show UUID

If you know your feed URL or podcast GUID, ask the assistant to run op3_get_show with it and it will return your UUID. You can also read the UUID from your show's OP3 stats page URL: https://op3.dev/show/{showUuid}.

3. Configure your MCP client

Claude Code

Add to your .mcp.json:

json
{  "mcpServers": {    "op3": {      "command": "npx",      "args": ["-y", "@conorbronsdon/op3-mcp"],      "env": {        "OP3_API_TOKEN": "your-op3-token"      }    }  }}
Claude Desktop

Add to your claude_desktop_config.json:

json
{  "mcpServers": {    "op3": {      "command": "npx",      "args": ["-y", "@conorbronsdon/op3-mcp"],      "env": {        "OP3_API_TOKEN": "your-op3-token"      }    }  }}

4. Verify

Ask your assistant: "Look up my show on OP3" with your feed URL, then "How many downloads did it get last month?"

Adding the OP3 prefix (if you are not on OP3 yet)

OP3 only has data once downloads route through its prefix. To start:

  1. In your podcast host, prepend https://op3.dev/e/ to your episode audio URLs. Many hosts (Transistor, Buzzsprout, and others) have a one-click OP3 toggle. Check your host's settings for an "OP3" or "analytics prefix" option.
  2. New downloads will start being logged. Historical downloads from before you added the prefix are not backfilled.
  3. Find your show on https://op3.dev and note its stats page URL, which contains your show UUID.

Limitations

Read these so you know what the numbers mean.

  • Geography is a computed sample, not an exact total. OP3 has no country-level aggregate endpoint. op3_top_countries pulls raw download records and counts them by country on the client side. The result is representative, not a precise lifetime figure. OP3 returns raw records oldest-first, so the tool defaults to the last 90 days (window_days) when you do not pass an explicit start — otherwise the sample would be the show's oldest downloads, not recent listeners. Within the window, records are still sampled oldest-first, so on a high-volume show a max_records sample skews toward the start of the window; the response includes sampleHitCap so you can tell when the window held more records than were sampled. Raise max_records (cap 20000) for a larger, more representative sample at the cost of speed and rate-limit headroom.
  • No device breakdown tool. OP3's raw records include a deviceType and deviceName, but there is no aggregate device query. You can see per-record device info via op3_downloads_timeseries. App share is available and exposed through op3_top_apps.
  • Top apps covers the last three calendar months only. That window is fixed by OP3, not configurable.
  • Data starts when the prefix was added. OP3 cannot report on downloads that never went through its redirect.
  • Bots are excluded by default in OP3's download queries, which is usually what you want.
  • Rate limits are not publicly documented. Keep limit and max_records modest. The server surfaces a clear error on HTTP 429.

Typed errors

API failures are mapped to a typed error hierarchy (OP3APIError base, with AuthError, RateLimitError, NotFoundError, ValidationError, and ServerError subclasses keyed off HTTP status) in src/errors.ts:

  • AuthError (401/403) — the OP3 token is missing or invalid.
  • RateLimitError (429) — too many requests against the OP3 API.
  • NotFoundError (404) — the show, feed, or resource doesn't exist (or isn't on OP3 yet).
  • ValidationError (400) — a malformed or invalid request parameter.
  • ServerError (5xx) — a failure on OP3's side; the specific status (500, 502, 503, ...) is preserved in the message.
  • OP3APIError — the base class, used as a fallback for unmapped status codes or network failures.

Every tool call still returns the same isError: true response shape on failure — the typed hierarchy just makes the message specific to what went wrong instead of a single generic "API error" string.

Development

bash
git clone https://github.com/conorbronsdon/op3-mcp.gitcd op3-mcpnpm installnpm run buildnpm test

Run locally:

bash
OP3_API_TOKEN=your-token npm start

Tests mock fetch and make no network calls.

Contributing

Issues and pull requests are welcome. If an OP3 endpoint changes shape, or there is an aggregate query worth wrapping as a tool, open an issue describing what you want and the OP3 endpoint it maps to. Keep the read-only contract: this server reports analytics, it does not change anything.

About

Built and maintained by Conor Bronsdon. I host the Chain of Thought podcast, which covers AI infrastructure, developer tools, and how practitioners actually use this stuff. I built this to pull honest listener analytics into the agent workflows that run the show.

Companion tools:

  • podcast-benchmark: benchmark your show against peers on public signals. The public-data complement to your own private OP3 analytics here.
  • Transistor MCP: Transistor.fm's official MCP server. Episodes, publishing, and analytics.
  • substack-mcp: read posts and manage drafts on Substack, safe for agent workflows.
  • podcastindex-mcp: the Podcast Index MCP server, search by person or topic, trending shows, feed health.
  • ai-tools-for-creators: a curated list of AI skills and MCP servers for people who ship ideas for a living.

More at chainofthought.show and on X.


Disclaimer

This is an independent personal project, not affiliated with, sponsored by, or endorsed by any company. All views expressed are my own.

License

MIT

來源:README.md,提交 cfe6314

工具

0
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版本歷史

1
  1. v0.2.0最新Sep 16, 2026

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