
linkedin-buying-signals
Find B2B prospects showing buying signals on LinkedIn and draft the outreach.
What it can do
What data it sees
Do you need an account
No: the server works without sign-in
Find B2B prospects showing buying signals on LinkedIn and draft the outreach.
How to connect
How to connect linkedin-buying-signals to Claude
The server address to paste into Claude settings:
https://www.getcleed.com/api/mcp
- Open Claude (claude.ai or the desktop app).
- Go to Settings → Connectors.
- Click Add custom connector.
- Paste the server address copied below into Remote MCP server URL and click Add.
- In a chat, click + → Connectors and switch the new connector on.
Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.
Authorization
After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.
How to connect linkedin-buying-signals to ChatGPT
The server address to paste into ChatGPT settings:
https://www.getcleed.com/api/mcp
- Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
- Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
- Open Settings → Connectors and click Create.
- Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
- Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
- In a new chat open + → Apps/Connectors and enable the connector.
OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.
Authorization
On first use ChatGPT opens the service's sign-in window. Sign in and approve access.
How to connect linkedin-buying-signals to Cursor
The server address to paste into Cursor settings:
https://www.getcleed.com/api/mcp
Fastest: click Open in Cursor below and confirm the prompt.
Manually:
- In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
- Paste the JSON copied below into
~/.cursor/mcp.json(per project:.cursor/mcp.jsonin the repo root). - Save the file. The server appears in the MCP list; authorize it there if asked.
Authorization
If the service needs sign-in, an authorize button appears next to the server in the MCP list.
Server tool list (15)
Raw names from tools/list. Only developers need these.
| list_prospects | Search the saved prospects in the account. Filter by company, industry, job title, country, signal type, minimum number of signals, whether an email address is known, enrichment state, or whether they have been contacted. Ordered by signal count, then most recently saved. |
| get_prospect | Everything known about one prospect: role, company, location, language, every detected signal with the verbatim quote from its source and the LinkedIn URL it came from, any existing email or LinkedIn draft, and outreach state. |
| get_pipeline_stats | How the pipeline stands: how many prospects, how many carry signals, enrichment state, how many have an email address, how many were contacted, what was added in the last 7 days, the most common signal types, and the remaining plan quota. |
| list_signals | The buying signals this account looks for: the predefined ones and the custom ones, each with the definition used to detect it and whether it is enabled. Use the returned type values with list_prospects and find_leads_from_signals. |
| get_icp | The active ICP: target roles, industries, countries, company sizes, relevant keywords and any exclusions. This is what sourcing and scoring filter against. |
| add_leads_from_urls | Save LinkedIn profiles as prospects and enrich them (name, role, company, industry, location, language). Skips anyone already saved. Counts against the import quota. |
| find_leads_from_signals | Search recent LinkedIn posts on the topics of this account's own signal definitions, keep only posts a check can prove are on topic, and return the people who wrote, commented on or reacted to them, filtered against the ICP (role, industry, country) and ranked. Nothing is saved: pass the returned candidates to import_sourced_leads. Spends a little of the monthly sourcing budget. |
| import_sourced_leads | Save candidates returned by find_leads_from_signals. They arrive already enriched and with the signal attached, including the verbatim quote from the post that surfaced them. Counts against the import quota. |
| analyze_prospects | Run the signal pipeline on prospects: enrich anyone missing company data, read their recent LinkedIn activity, and detect buying signals. Every signal kept must quote its source verbatim. Counts against the monthly analysis quota. Slow: expect up to a few minutes. |
| draft_email | Write a personalised email for a prospect, built from their detected signals, in their language. Saves the draft on the prospect and returns it. Does not send. |
| draft_linkedin_message | Write a short LinkedIn connection note for a prospect from their detected signals, in their language. Saves the draft and returns it. Does not send. |
| send_email | Send an email to a prospect from the connected mailbox. This reaches a real person immediately and cannot be undone. Pass the subject and body you want sent, or omit them to send the saved draft. Requires a mailbox connected in getcleed under Integrations. |
| send_linkedin_message | Send a LinkedIn connection request with a note to a prospect from the connected LinkedIn account. This reaches a real person immediately and cannot be undone. Pass the note you want sent, or omit it to use the saved draft. Requires LinkedIn connected in getcleed under Integrations. |
| mark_email_sent | Record that a prospect was emailed outside getcleed, so reporting and follow-ups stay correct. |
| create_custom_signal | Teach the account a new buying signal to look for, described in plain language (for example "people complaining their onboarding takes too long"). Future analyses and sourcing will use it. |