> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pipecorn.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Example workflows

> Prompts you can give an assistant connected to Pipecorn, and the tools it chains to answer them.

Here are some examples of what you can ask your AI assistant once the
Pipecorn MCP server is connected, with the tools it typically chains behind
the scenes.

## People enrichment

> Find the workers at Pipecorn and find their phones and emails.

The assistant uses `enrich_account` to find Pipecorn's LinkedIn ID, then
`search_leads_in_company` to list employees, then `bulk_enrich_contacts` to
retrieve their emails and phones.

## Targeted prospecting

> Find the \[job title] of \[industry] companies in Paris.

The assistant uses `search_locations` to get the Paris location ID and
`search_industries` to resolve the industry, then `search_accounts` to find
matching companies, then `search_leads_in_company` to find the \[job title] at
each company, then `bulk_enrich_contacts` to retrieve their emails and phones.

## Size a segment before spending credits

> How many VPs of Sales at fintech companies with 51 to 200 employees are there in the UK? Don't run anything yet.

The assistant uses `preview_advanced_search_leads`, which is free, and reports
the count and a sample. Ask it to run `advanced_search_leads` once you are
happy with the segment, and to check `get_credits` first if you plan to enrich
the results.

## Build a Sales Navigator list

> Create a list called "Q4 targets" with Stripe, Adyen and Mollie.

The assistant uses `create_list` with the three companies, then `get_list` to
confirm what was pushed to Sales Navigator.

## Watch who engages with a post

> Who reacted to or commented on this LinkedIn post? \[post URL]

The assistant uses `extract_post_engagers`, then offers to enrich the engagers
with `bulk_enrich_contacts`.

See the [tool reference](/mcp/tools) for everything the assistant can call.