原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Coresignal MCP

作者:Coresignal-com版本 2.0.0i★ –i在云端运行
注册名称com.coresignal/mcp

安装

概览

作者提供的说明(英文原文)

Fresh company, employee, and jobs records in real time.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://mcp.coresignal.com/mcp/v2

在终端中运行这条命令

claude mcp add --transport http coresignal https://mcp.coresignal.com/mcp/v2

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "coresignal": {
      "url": "https://mcp.coresignal.com/mcp/v2"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "coresignal": {
      "type": "http",
      "url": "https://mcp.coresignal.com/mcp/v2"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://mcp.coresignal.com/mcp/v2

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 coresignal.com 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32725 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32725 个服务器的 22% 更新
  • 基础检查结果等于或优于此分类中其他 32725 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Coresignal MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.0.0)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Signoff

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Signoff

作者:ayuanxx-max

Five gates that make an agent's 'done' provable: run them, read the verdict, audit the record.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Coresignal MCP v2

The official Model Context Protocol server for Coresignal — bring fresh B2B data on 895M+ employees, 70M+ companies, and 468M+ job postings straight into your AI assistant.

https://mcp.coresignal.com/mcp/v2

Search in plain natural language, pull full records, enrich contacts with verified emails, and export large result sets as downloadable files — all from Claude, Cursor, Codex, VS Code, or any other MCP-compatible client.


Features

  • OAuth 2.1 authentication — sign in with your Coresignal dashboard account; no API keys in config files.
  • Natural-language search with match evidence in every result row, so you can see *why* each record matched.
  • Cost transparency — every response reports credits_consumed, and expensive calls ask for confirmation before spending.
  • Field discovery — entity_fields finds the right field names by keyword, free, without loading the full 300+ field vocabulary into context.
  • File downloads — large result sets are stored server-side and returned as a download link instead of flooding the chat.
  • `artifact_read` pages delivered files back into the conversation for free — works even in clients with no filesystem access.

Prerequisites

  • A Coresignal account with an active subscription (credits) and a team API key provisioned in the dashboard. The MCP server resolves your team's key automatically after sign-in — you never paste it into a config file. No subscription yet? Start with the 7-day free trial — it includes 2,000 credits. See the plan comparison.

On first connection your client opens a browser window to sign in to the Coresignal dashboard. That's the whole setup — no environment variables, no secrets.


Client setup

Claude Desktop

Claude Desktop supports remote MCP servers natively via Connectors:

  1. Open Settings → Connectors → Add custom connector.
  2. Name: Coresignal, URL: https://mcp.coresignal.com/mcp/v2.
  3. Click Add, then Connect — a browser window opens to sign in to your Coresignal dashboard account.

Important — enable file downloads: Claude Desktop blocks downloads from domains it doesn't know. To download result files (large fetches are delivered as links), add mcp.coresignal.com to the Domain allowlist in Claude Desktop settings (on Team/Enterprise plans your admin manages this). Without it, download links from the server will be blocked — though you can always read the data back in-chat with the free artifact_read tool instead. See File downloads.

Claude Code

claude mcp add --transport http coresignal https://mcp.coresignal.com/mcp/v2

Then inside a session run /mcp, select coresignal, and complete the browser sign-in. Re-run /mcp any time you need to re-authenticate.

Codex (OpenAI Codex CLI)

codex mcp add coresignal --url https://mcp.coresignal.com/mcp/v2

A browser window opens to sign in to your Coresignal dashboard account.

Cursor

Add to ~/.cursor/mcp.json:

{

"mcpServers": { "coresignal": { "url": "https://mcp.coresignal.com/mcp/v2" } } }

Cursor detects that the server requires authentication and shows a Needs login prompt — click it to complete the browser sign-in.

OpenCode

Add Coresignal MCP:

opencode mcp add coresignal --url https://mcp.coresignal.com/mcp/v2

Authenticate:

opencode mcp auth coresignal

A browser window opens to sign in to your Coresignal dashboard account.

Visual Studio Code

Run MCP: Add Server from the Command Palette, choose HTTP, and enter the URL — or add to .vscode/mcp.json:

{

"servers": { "coresignal": { "type": "http", "url": "https://mcp.coresignal.com/mcp/v2" } } }

VS Code prompts you to authorize the server on first use and handles the OAuth flow in your browser.

Cline

Add to ~/.cline/data/settings/cline_mcp_settings.json:

{

"mcpServers": { "coresignal": { "type": "streamableHttp", "url": "https://mcp.coresignal.com/mcp/v2", "disabled": false } } }

Open Cline MCP interface:

cline mcp

From menu select Authorize OAuth and select coresignal. Cline will handle the OAuth flow in your browser.


File downloads & the domain allowlist

Large results (and any call with delivery="url") are not dumped into the chat to save LLM input tokens. Instead the server stores the rows as a file and returns a signed HTTPS download link that expires after 1 hour:

{

"delivery": "url", "url": "https://mcp.coresignal.com/mcp/v2/artifacts/…?exp=…&sig=…", "artifact_name": "employee_fetch-baf941dd4f8c4dfe.jsonl", "count": 500, "credits_consumed": 10000 }

From here, the agent gets at the data in one of three ways:

  1. The agent downloads the file itself — in clients with shell access, the agent will typically curl the link to disk and analyze the file locally with grep/jq/pandas.
  2. The agent reads it back in-chat — in clients with no shell and no filesystem, the agent calls artifact_read(artifact_name, offset, limit) instead, paging through the file in slices over the MCP session. This is free and works everywhere, so nothing floods the chat.
  3. You download it manually — if the agent itself isn't allowed to fetch the link (domain not allowlisted, sandbox without network access), click the link, save the file, and tell the agent where it is: *"I've downloaded the file to ~/Downloads/employee_fetch-….jsonl — analyze it from there."* Works in any client that can read local files.

Prefer the download when your client supports it. artifact_read is free in Coresignal credits, but not in LLM tokens: every page it returns becomes part of the conversation and is re-billed as input tokens on each subsequent turn. Each page is also trimmed to a fixed token budget — a full employee record is ~8k tokens, so a single page carries only a handful of full records regardless of the limit you ask for. Reading a large file that way takes hundreds of calls and can exhaust the context window before you reach the end. A downloaded file costs essentially no tokens — the assistant can filter thousands of rows locally with grep/jq and surface only the answer. That's why it pays to get downloads working up front (domain allowlist, sandbox network access) and keep artifact_read for clients that can't download or for eyeballing a few rows.

If downloads are blocked, nothing is lost: the records are already stored and paid for — read them with artifact_read. Never re-run a fetch to "recover" a file; that bills every record a second time.


Tools

ToolWhat it doesCost
entity_searchNatural-language search over employees, companies, or jobs20 credits per search (flat)
entity_fieldsKeyword search over an entity's ~300 field namesFree
entity_fetchPull full (JSONL) or projected records, by search handle or by id20 credits per employee/company record, 1 per job record
email_enrichVerified business emails for employee ids (CSV)10 credits per email found (misses are free)
artifact_readPage rows back out of a delivered fileFree
entity_search

Searches employee, company, or job records with a plain-language query:

*"Senior Python developers at fintech companies in French"*

Every call costs a flat 20 credits and returns:

  • total_count — the exact number of records the query matched,
  • up to 20 preview rows (limit=0 returns just the count), each showing the fields the query matched on — the *evidence* for why each result is there,
  • a cache_id — a 1-hour handle to the search that saves credits and time: pass it to entity_fetch and the matched records are collected straight away — no need to re-run (and re-pay for) the search, and resolving the cache_id itself is free. Record ids stay server-side, so nothing bulky ever passes through the conversation.
entity_fields

Free, instant lookup of field names by meaning — "salary" finds the compensation fields, "current job title and seniority" finds active_experience_title, experience.position_title, etc. Use it to build the fields list for a custom-scope fetch without ever loading the full field vocabulary into context.

entity_fetch

Collects records — either up to 20 hand-picked ids from search results, or up to 1,000 records per call via a cache_id. Billing is per record found: 20 credits for employees/companies, 1 for jobs.

email_enrich

Verified, deliverable business emails for up to 1,000 employee ids — 10 credits per email found; not-found ids are free. EEA/UK contacts are not accessible (GDPR).

artifact_read

Reads a delivered file back over the authenticated MCP session, a page at a time — free, since the records were billed when they were fetched. This is what makes file delivery work everywhere, including chat clients that can't open a link or touch a filesystem.


Example prompts

Market scan

*"Find B2B SaaS companies in the Nordics with 50–200 employees that raised funding in the last two years."*

Build a lead list with verified emails

*"Search for heads of data at US companies with 500+ employees. Fetch 20 full profiles to a file with verified emails."*

Deep-dive a single company**

*"Pull the full record for flo.health — funding rounds, headcount growth, and current job openings."*

...


Credits & billing

ActionCredits
entity_search (any limit, including 0)20 per search
entity_fetch — employee or company20 per record found
entity_fetch — job1 per record found
email_enrich10 per email found; misses free
entity_fields, artifact_readFree

Every response includes credits_consumed — the actual billed amount, so a discrepancy (sent 1,000 ids, billed for 950 records) tells you exactly how many ids weren't found. The server never spends silently: fetches confirm field scope with you first, and a fetch that can't be delivered fails *before* any credits are spent.

Credits are drawn from your team's Coresignal subscription — manage keys and billing in the dashboard. New to Coresignal? The 7-day free trial comes with 2,000 credits — that's 100 searches, or 100 employee/company records, or a mix — see the plan comparison.

Links

问 PopNx