Coresignal MCP Server

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.

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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.

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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.

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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.

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Tools

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.

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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."

...

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Credits & billing

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

• Coresignal — data coverage, plans, and pricing
• Coresignal dashboard — account, team, API keys, credits
• API documentation — the underlying data APIs