{"id":50602,"date":"2026-11-02T20:46:39","date_gmt":"2026-11-02T17:46:39","guid":{"rendered":"https:\/\/snov.io\/knowledgebase\/?p=50602"},"modified":"2026-11-03T12:49:05","modified_gmt":"2026-11-03T09:49:05","slug":"enrichment-workflows-in-snov-io-mcp","status":"publish","type":"post","link":"https:\/\/snov.io\/knowledgebase\/enrichment-workflows-in-snov-io-mcp\/","title":{"rendered":"Enrichment workflows in Snov.io MCP"},"content":{"rendered":"

This guide shows four data enrichment<\/a> workflows you can run from your AI tool with Snov.io MCP.<\/a><\/p>\n

Fill in emails and phone numbers, add LinkedIn data, research prospects and companies, and add results directly to your lists.<\/p>\n

Each workflow runs several enrichment actions in sequence. Describe the goal in plain words, and the assistant runs the actions after you confirm the cost.<\/p>\n

Choose a workflow<\/a>
\nWorkflow 1. Fill in emails and phone numbers<\/a>
\nWorkflow 2. Add LinkedIn data to a list<\/a>
\nWorkflow 3. Research companies and find a reason to reach out<\/a>
\nWorkflow 4. Clean list data before outreach<\/a>
\nSave prompts and manage columns<\/a>
\nNext steps<\/a><\/p>\n

\n
\"learn\"<\/div>\n
\n

Before you start. <\/strong>To run these workflows, make sure you have:<\/p>\n

1. Snov.io connected to your AI tool.<\/strong> Follow this guide<\/a> to connect it.<\/p>\n

2. A prospect list that you own.<\/strong> Only the list owner can run enrichment.<\/p>\n

3. Enrichment tokens.<\/strong> Read this guide<\/a> to learn how tokens work.<\/p>\n

4. Starting data for each prospect.<\/strong> Each workflow lists what it needs.<\/p>\n<\/div>\n<\/div>\n

Every workflow follows the same run pattern: check the cost, test on three to five prospects, then run the whole list. Read this guide<\/a> for those steps and for checking progress.<\/p>\n

Choose a workflow<\/strong><\/h2>\n
\n\n\n\n\n\n\n\n\n
Workflow<\/th>\nUse it to<\/th>\nCost per prospect (tokens<\/a>)<\/th>\n<\/tr>\n<\/thead>\n
Fill in emails and phone numbers<\/a><\/td>\nAdd contact details to a list, and call only the prospects that matter<\/td>\nEmails: 5 per email found.
\nPhone numbers: 10 per number found with Wiza, or 22 with Zeliq, which has wider coverage.<\/td>\n<\/tr>\n
Add LinkedIn data to a list<\/a><\/td>\nPull profile details and extra LinkedIn data into separate columns<\/td>\nProfile details: 1 with the Snov.io database, or 4 with Generect.
\nExtra data: the assistant shows the price before the run.<\/td>\n<\/tr>\n
Research companies and find a reason to reach out<\/a><\/td>\nGive each prospect one company-specific line for outreach<\/td>\nCompany details: 1.
\nWeb research: about 4.8 with the recommended model.
\nClean and edit: 1.
\nTotal: about 6.8.<\/td>\n<\/tr>\n
Clean list data before outreach<\/a><\/td>\nStandardize company names, job titles, and locations<\/td>\n1 token per prompt. You are charged only for newly generated or updated data.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Workflow 1. Fill in emails and phone numbers<\/strong><\/h2>\n

Add contact details to a list, and spend phone tokens only on the prospects you plan to call.<\/p>\n

Email search needs a LinkedIn URL, or a first name, last name, and company domain or name. Phone search also works with a first name, last name, and email.<\/p>\n

Find emails for prospects without one<\/strong><\/h3>\n

Ask for a search of only the prospects that have no email yet. The assistant shows the cost and the provider options before it runs.<\/p>\n

\n
Find emails for everyone in my list [List name] who doesn't have one yet.<\/div>\n<\/div>\n

<\/p>\n

Find phone numbers for priority prospects<\/strong><\/h3>\n

Phone searches cost more than email searches, so run them on a short list. Name the accounts you plan to call.<\/p>\n

\n
Find direct phone numbers for the prospects in [List name] who work at [Company 1], [Company 2], and [Company 3].<\/div>\n<\/div>\n

Data you get<\/strong><\/h4>\n

Found emails and numbers appear in the Email<\/strong> and Phone number<\/strong> columns of your list. To check which prospects returned a result, run the prompt below. It lists each prospect as found, not found, or in progress, with the saved emails and numbers.<\/p>\n

\n
Which prospects in [List name] got an email or phone from enrichment?<\/div>\n<\/div>\n

<\/p>\n

\n
\"note\"<\/div>\n
You are charged only when an email or a phone number is found.<\/div>\n<\/div>\n

Workflow 2. Add LinkedIn data to a list<\/strong><\/h2>\n

Pull profile details and extra LinkedIn data into your list, then move the values you need into their own columns.<\/p>\n

A LinkedIn URL works best. The Snov.io database also accepts a first name, last name, and company domain or email. Generect needs a LinkedIn URL or an email.<\/p>\n

Pull profile details<\/strong><\/h3>\n

Choose the Snov.io database option, which updates monthly, or the real-time option from Generect, which pulls live LinkedIn data.<\/p>\n

\n
Pull the LinkedIn profile details for the prospects in [List name].<\/div>\n<\/div>\n

<\/p>\n

Pull extra LinkedIn data<\/strong><\/h3>\n

Each run adds one data type: publications, patents, awards, recommendations, profile activity, or similar profiles.<\/p>\n

\n
Pull recent LinkedIn activity for the prospects in [List name].<\/div>\n<\/div>\n
\n
\"tip\"<\/div>\n
Run this step again with a different data type to add more context to the same list.<\/div>\n<\/div>\n

Extract the values you need into separate columns<\/strong><\/h3>\n

Profile and company enrichments store many values in one bulk column.<\/p>\n

This step extracts data from that column into a single column, such as job title, company name, or start date from the work history. Extracting values spends no tokens. Read this guide<\/a> to learn more about prospect data in Snov.io.<\/p>\n

\n
Copy each prospect's current job title into a new column.<\/div>\n<\/div>\n

<\/p>\n

Data you get<\/strong><\/h4>\n

Each value sits in its own column. Use those columns as variables in campaign emails and LinkedIn messages, as described in this guide<\/a>.<\/p>\n

Workflow 3. Research companies and find a reason to reach out<\/strong><\/h2>\n

Give each prospect one short, company-specific line for outreach.<\/p>\n

Each prospect needs a company domain, company name, or company LinkedIn URL. Prospects with none of these are skipped.<\/p>\n

Get company details<\/strong><\/h3>\n

This adds industry, size, location, specialties, funding, and similar companies to each prospect.<\/p>\n

\n
Get company details for every prospect in [List name].<\/div>\n<\/div>\n

Research each company on the web<\/strong><\/h3>\n

Ask for one specific fact and a column name. The assistant shows the cost for the default model and for cheaper models before it runs. See this guide<\/a> for more research prompts.<\/p>\n

\n
Find the latest funding news for each company in [List name] and summarize it in one sentence. Save it to a column called Company news.<\/div>\n<\/div>\n
\n
\"note\"<\/div>\n
Web research charges tokens for every prospect, even when no public data is found.<\/div>\n<\/div>\n

<\/p>\n

Turn the research into one outreach line<\/strong><\/h3>\n

This step uses Clean and edit to read the research column and write the line you can use in a message. Prospects with No data found have no news to mention, so skip them in outreach.<\/p>\n

\n
Using the Company news column in [List name], write one sentence about what changed at the company.
\nIf the column has no news, return No data found.
\nSave the result to a column called Outreach reason.<\/div>\n<\/div>\n
\n
\"tip\"<\/div>\n
Ask which enrichment columns and prompt variables the list has before you write a prompt that uses them.<\/div>\n<\/div>\n

<\/p>\n

Data you get<\/strong><\/h4>\n

The Outreach reason<\/strong> column holds one sentence per prospect. Use it as a variable in your first email line.<\/p>\n

Workflow 4. Clean list data before outreach<\/strong><\/h2>\n

Standardize company names, job titles, and locations with one prompt per field.<\/p>\n

You need at least one existing column with the data you want to change. Each prompt saves its result to a column.<\/p>\n

Clean company names<\/strong><\/h3>\n
\n
Clean the company names in [List name]: remove Inc, LLC, and extra symbols.<\/div>\n<\/div>\n

<\/p>\n

Reformat locations<\/strong><\/h3>\n
\n
Write each location in [List name] as City, Country.<\/div>\n<\/div>\n

Review the cleaned values<\/strong><\/h3>\n

Ask for a few prospects before and after cleanup.<\/p>\n

\n
Show the original and cleaned company names for 5 prospects in [List name].<\/div>\n<\/div>\n

Save prompts and manage columns<\/strong><\/h2>\n

Save a prompt that works, so you can run it again on any list. Preset prompts for research, data cleanup, and personalization appear next to your own.<\/p>\n

\n\n\n\n\n\n\n\n\n\n
What you want to do<\/th>\nPrompt example<\/th>\n<\/tr>\n<\/thead>\n
Save a prompt for reuse<\/td>\nSave this prompt as a template called Company name cleanup.<\/td>\n<\/tr>\n
Browse saved prompts<\/td>\nShow my saved enrichment prompts.<\/td>\n<\/tr>\n
Favorite a prompt<\/td>\nMark my Company name cleanup prompt as a favorite.<\/td>\n<\/tr>\n
Create a column<\/td>\nCreate a column called Company size in my list [List name].<\/td>\n<\/tr>\n
Rename a column<\/td>\nRename the Company size column in [List name] to Employee range.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Preset prompts can only be marked as favorites. You can edit or delete your own prompts. Deleting a column removes it with all its values, so the assistant asks you to confirm first.<\/p>\n

Next steps<\/strong><\/h3>\n