Publication Cadence Tracker MCP Server

Publication Cadence Tracker MCP Server

Tracks a company's long-form publication cadence per month and trend (accelerating, steady, declining, dormant) from a given domain. Provides detailed metrics like post counts, trend percentage change, formats detected, and reliability flags.

Category
访问服务器

README

Publication Cadence Tracker MCP Server

npm MCP License: MIT

MCP server for the Mamba Labs Publication Cadence Tracker actor on Apify.

Give it a company domain. It tells your agent how much long-form work that company publishes per month, and whether that rate is rising or falling.

Tool

track_publication_cadence

Returns a flat row per domain: posts_last_30d, posts_last_90d, posts_last_12m, avg_posts_per_month, cadence_trend (accelerating, steady, declining, dormant, unknown), trend_pct_change, most_recent_post_date, days_since_last_post, blog_url, formats_detected[], distinct_authors_count, discovery_method, confidence, and an evidence[] array of quotable strings.

Why the trend and not the count

Four pieces a month is unremarkable. Going from four to twelve in six months is a content operation outgrowing its staff. The comparison is stated rather than implied: the last 90 days against the prior 275 days, both normalized to posts per month, with accelerating and declining set at 25 percent either way.

This is editorial output volume, not changelog monitoring. A release feed is detected and rejected rather than counted as published work.

The number it refuses to give you

Publication dates come from the post pages, never from sitemap lastmod. Across 100 measured URL pairs, lastmod tracked the page's own dateModified and ran later than datePublished by a median of 151 to 1653 days on four of six sites. A cadence built on it would report a company that refreshed 200 old posts as a company that published 200 posts.

A page field can fail the same way, so it is checked against its own distribution and against the site's feed. When it fails, date_source_reliable comes back false and every count is nulled. Check that field before quoting a number.

Measured on nine live domains: a rate recovered on 5 of 6 publishers, 3 of 3 controls correctly returning nothing. The one miss is the guard refusing a site whose date field tracks edits.

track_publication_cadence

Input Type Notes
domain string One company domain.
domains string[] Batch. Takes precedence over domain.
max_pages_to_date integer Post pages fetched per domain, default 400. Above this the counts are estimated from an even sample.
domain_time_budget_ms integer Hard per-domain wall-clock ceiling, default 75000.
batchSize integer Concurrent domains, default 2.
skipCache boolean Ignore the 3 day result cache.

What it actually measures

Not whether a company has a blog. How much it published, when, and whether the rate moved.

Finding the blog is most of the work, and it is where a naive version fails. The blog often lives on a different host from the apex and the apex sitemap never mentions it (blog.hubspot.com). A homepage sometimes advertises only a changelog feed while linking to the real blog repeatedly (about.gitlab.com). Paths are often locale prefixed, so /en-uk/ and /bg-bg/ fragment the archive into forty pieces. All three are handled, and blog_url reports a locale-prefixed section as https://example.com/*/knowledge/.

Three fields to read before you trust a number. date_source_reliable false means the site's date field tracks edits rather than publication and every count has been nulled. counts_are_estimate true means the archive was larger than the page budget and the counts come from a scaled even sample, so two runs can differ by a few posts. partial_result true means the wall-clock budget stopped the crawl and the numbers are lower bounds.

Setup

{
  "mcpServers": {
    "mamba-publication-cadence-tracker": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-publication-cadence-tracker"],
      "env": { "APIFY_TOKEN": "your-apify-token" }
    }
  }
}

Get a token at console.apify.com/account/integrations. Read-only; consumes Apify credits per domain analyzed.

Also available

This tool is also exposed by the GTM Suite umbrella server, alongside the rest of the Mamba Labs GTM actors, if you would rather run one server than many.

Built by Mamba Labs.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选