Lusha MCP. Pull verified emails and phone numbers directly from your AI client.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Lusha connects your AI agent directly to verified B2B contact data. Use it to find emails, direct phone numbers, and company details for any prospect without ever opening the Lusha platform.
It lets you build targeted lead lists or enrich CRM records instantly via tool calls.
What your AI agents can do
Bulk enrich
Enriches multiple contacts at once by fetching verified emails and phone numbers from a list of data.
Find by linkedin
Retrieves contact details (email, phone) for any person given their full LinkedIn profile URL.
Find company
Pulls firmographic data and general details about a company based on its name or identifier.
The agent locates verified emails, direct dials, and mobile numbers for a specific person.
It pulls structured company information like revenue range, employee count, and industry sector.
You build targeted prospect lists using filters such as job title, seniority level, or geographic location.
The tool can enrich multiple contacts simultaneously from existing data sets or CRM exports.
It matches and returns contact details using a specific LinkedIn URL.
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Lusha MCP Server: 6 Tools for Sales Intelligence
These tools let your AI client find and validate B2B contact information, company details, and prospect data from a single source.
019d75cbbulk enrich
Enriches multiple contacts at once by fetching verified emails and phone numbers from a list of data.
019d75cbfind by linkedin
Retrieves contact details (email, phone) for any person given their full LinkedIn profile URL.
019d75cbfind company
Pulls firmographic data and general details about a company based on its name or identifier.
019d75cbfind person
Finds the verified contact details—email, phone, social links—for any specific individual person.
019d75cbget credits
Checks your current usage status and remaining credit balance for the service.
019d75cbsearch contacts
Searches a large database of contacts by applying multiple filters like job title, company size, or geography.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Lusha, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
You connect your AI agent directly to verified B2B contact data using Lusha's tools. It lets you pull emails, direct phone numbers, and company details for any prospect without ever having to open the actual Lusha platform itself.
Finding People:
When you need specific contact info for an individual, your agent can use find_person to locate verified email addresses, direct dial phones, and social media links for a person. You also don't have to rely on LinkedIn; if you feed the agent a full LinkedIn profile URL, it uses find_by_linkedin to match and return that same contact data—the email and phone numbers.
For even bigger targets, your AI client can use search_contacts, which lets you build highly specific prospect lists by applying filters like job title, company size, or geographic location.
Gathering Company Intel:
Need to know more about the business? The agent uses find_company to pull firmographic data and general details on any company just from its name or identifier. This gives you structured information like what industry sector they're in, their revenue range, how many employees they have, and where they're headquartered.
Processing Large Batches:
If you've got a whole list of contacts—maybe it’s a CRM export or some messy spreadsheet—the agent doesn't stop at one person. It uses bulk_enrich to enrich multiple contacts simultaneously, fetching verified emails and phone numbers for the entire batch in one go.
Using It:
Your AI client simply calls the appropriate tool—say, find_person(name='John Doe', company='Acme Corp') or search_contacts(job_title='VP Sales'). The server executes the action and hands the results back directly to your agent. You never have to copy/paste anything into a web interface.
Checking Credits:
If you're running deep searches, your agent can use get_credits to check your current usage status and how many credits you've got left for the service. It keeps you in the know so you don't run out of juice mid-campaign.
It’s all about direct tool calls. You tell your agent what data you need—a person, a company, or a whole list—and it gets that verified B2B data back instantly.
How Lusha MCP Works
- 1 Subscribe to the Lusha integration on the marketplace.
- 2 Copy your API key from your Lusha dashboard (Settings → API).
- 3 Ask your AI agent to call a tool, like
find_personorsearch_contacts, passing only the necessary criteria.
The bottom line is that your AI client executes the lookup in the background and returns structured data directly into your chat or code environment.
Who Is Lusha MCP For?
Anyone who relies on finding high-quality, verified B2B contact data hates manual research. This tool is for Sales Development Reps (SDRs) and Account Executives (AEs) whose job depends on cold outreach hitting the right person with a working email. It's also essential for Recruiters building candidate pipelines.
Uses search_contacts to build highly filtered lists of prospects and then runs find_person on the top targets to get verified emails before launching a campaign.
Enriches records in their CRM by running bulk_enrich across existing accounts to make sure they have the current direct dial number before calling.
Uses find_by_linkedin to quickly pull contact details for a candidate, bypassing the need to manually search multiple databases.
What Changes When You Connect
- Stop wasting time on bad data. Running
find_personinstantly gives you a person's verified email, direct dial number, and mobile—all in one tool call. - Boost CRM hygiene with
bulk_enrich. Instead of updating records one by one, process hundreds of leads at once from your existing list or export. - Target exactly who you need. Use
search_contactsto filter prospects by niche criteria (e.g., 'VP Sales' in 'FinTech') and get a ready-to-use shortlist. - Source candidates fast. If you have a LinkedIn profile, use
find_by_linkedin. It’s the fastest way to pull contact info without manual copy/pasting. - Get company context instantly. Use
find_companywhen you only know a business name; it provides industry, revenue range, and employee count.
Real-World Use Cases
The SDR needs to warm up a list of prospects
A new SDR has 100 company names. Instead of researching them manually, they ask their agent to run find_company on the batch. This gives immediate industry and revenue data, which helps them tailor their cold email pitch before running search_contacts for specific job titles.
Recruiting a passive candidate
A recruiter finds a great profile via LinkedIn but has no direct number. They ask the agent to use find_by_linkedin. The tool returns the verified mobile and email address, letting them skip the initial cold contact phase.
Updating stale CRM records
An AE opens a list of 50 accounts that haven't been contacted in six months. They send the list to their agent and call bulk_enrich. The tool verifies current emails and phone numbers, ensuring the next outreach attempt is accurate.
Identifying key decision-makers
A user needs a contact at a specific company but only knows the industry. They ask the agent to use search_contacts, filtering by 'Head of Marketing' and 'Healthcare.' The result provides direct dials for the top three matches.
The Tradeoffs
Manually researching contacts
Opening LinkedIn, copying a profile URL, going to Google, checking company websites, and trying to find an email address through multiple manual steps.
→
Just feed the request to your agent. If you have the URL, use find_by_linkedin. For basic info, try find_person first.
Trying to enrich data without a list
Attempting to guess which fields need updating or manually running lookups on single records when you actually have 50 names in Excel.
→
Use bulk_enrich. It takes your existing dataset and processes all the necessary verification steps across multiple contacts at once.
Relying solely on company name
Just searching for 'Tech Company X' without specifying a job title, leading to thousands of irrelevant results.
→
Always combine find_company with filters. Use search_contacts and specify the role (e.g., 'Director') alongside the company name.
When It Fits, When It Doesn't
Use this if your primary goal is finding, validating, or expanding B2B contact data (emails, direct dials, firmographics). You should use it when you're moving from a general idea ('I need to talk to someone at Company X') to an actionable step ('Here is the email for Jane Doe').
Don't use this if your goal is purely internal research (e.g., 'What was discussed in last week's meeting?') or if you only need public web data that doesn't involve a specific person or company record. If you just need general market trends, search engines are better. If you have an existing list of leads, use bulk_enrich to validate them before moving on.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Lusha. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding the right contact shouldn't require opening five different tabs.
Today, finding a single verified email address means bouncing between LinkedIn, ZoomInfo trial accounts, company 'Contact Us' pages, and then cross-referencing that information in your CRM. You copy this person’s name, paste it into Google to find the main site, click through three layers of menus, and finally—after 15 minutes—you get a guess at an email address.
With Lusha MCP, you just tell your agent: 'Get me the contact details for Jane Smith.' The tool handles all that messy cross-referencing in seconds. You get verified emails, direct phone numbers, and social links returned to you instantly.
Lusha MCP Server lets you build complete lead profiles.
Before, building a full profile required three separate actions: 1) Finding the company's basic info (using one service), 2) Finding the person’s name/title (another service), and 3) Trying to stitch those two pieces of data together manually. It was always fragmented.
Now, your agent runs a sequence—calling `find_company` first, then using that company context to run `search_contacts`. You get a single, rich object with everything attached, allowing you to move straight into outreach.
Common Questions About Lusha MCP
How do I get my Lusha API key? +
Log in to your Lusha account at dashboard.lusha.com. Click the Settings (gear icon) in the left sidebar. Navigate to the API section. Your API key is displayed on this page — click Copy to copy it. Paste it into the configuration field below. API access is available on Lusha's Premium and Scale plans.
Can I find phone numbers and emails for a specific prospect? +
Yes. Provide a person's name and company, and Lusha returns verified business email, personal email, direct dial, mobile number, and LinkedIn profile — all from its database of 100M+ business profiles.
How many credits does each search consume? +
Each contact enrichment uses 1 credit from your Lusha plan. Credits refresh monthly. Your AI agent reports remaining credits so you always know your usage — no surprises on your bill.
Is the data GDPR compliant? +
Yes. Lusha is ISO 27701 certified and GDPR/CCPA compliant. All contact data is sourced from publicly available information and community-contributed data with proper consent mechanisms.
If I use the Lusha tool, how does it handle large volumes of searches? +
The system manages volume by processing requests in controlled batches. You don't hit a hard limit; instead, the agent handles throttling automatically to ensure reliable data retrieval for your workflow.
What happens when I use `bulk_enrich` if some of my contacts fail validation? +
The process completes regardless of failures. The system processes every contact you provide, and the output report clearly flags which records failed and why they couldn't be enriched.
Aside from emails, what company data can Lusha retrieve using `find_company`? +
It provides detailed firmographics. You get industry classifications, revenue ranges, employee counts, and the corporate headquarters location for any given business entity.
What input format should I prepare when calling `bulk_enrich`? +
You must provide structured data, typically in a CSV or list format. The agent requires clear identifiers (like existing emails or company names) to match against the Lusha database for enrichment.
Multi-server workflows that include Lusha MCP
MCP Servers for Founder Background Checks
Founder claims verified, previous companies checked, team history validated , know who you are admitting before the program starts
Vet Founders Before You Invest Using MCP
Founder identity verified, track record pulled, red flags surfaced , vet the person behind the pitch before you wire the capital
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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