Bring B2b Intelligence
to LangChain
Learn how to connect Lusha to LangChain and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Lusha MCP Server?
Connect your Lusha account to any AI agent and take full control of your sales prospecting and data enrichment through natural conversation. Lusha provides a premier B2B database, and this integration allows you to retrieve high-fidelity contact details (email, phone), enrich company metadata, and search for new prospects directly from your chat interface.
What you can do
- Contact & Person Enrichment — Lookup detailed contact metadata programmatically using name, company, or LinkedIn URLs to ensure your CRM is always synchronized.
- Company & Firmographic Intelligence — Access and monitor company data including industry, revenue, and headcount directly from the AI interface to qualify accounts in real-time.
- Prospecting & Search Control — Search for new contacts and companies matching your Ideal Customer Profile (ICP) via natural language to drive better sales efficiency.
- Usage & Credit Oversight — Access granular details for your credit consumption and remaining balance using simple AI commands to maintain a clear overview of your resources.
- Operational Monitoring — Track system responses and manage data ingestion to ensure your sales workflows are always optimized.
How it works
1. Subscribe to this server
2. Enter your Lusha API Key from your dashboard settings
3. Start enriching your sales data from Claude, Cursor, or any MCP-compatible client
No more manual copy-pasting from LinkedIn profiles. Your AI acts as a dedicated sales researcher or lead qualification assistant.
Who is this for?
- Sales Development Reps (SDRs) — quickly retrieve phone numbers and monitor account health without switching apps.
- Account Executives — automate the enrichment of new leads and track prospecting progress via natural conversation.
- Marketing Teams — streamline the retrieval of firmographic metadata and monitor data quality directly within the chat.
Built-in capabilities (12)
Enrich multiple companies
Enrich multiple contacts
Get firmographics
Get contact details
Check connection
Check account balance
Enrich by email
Enrich by LinkedIn
Check API usage
Search for businesses
Search for contacts
Verify API key
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Lusha through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Lusha MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Lusha queries for multi-turn workflows
Lusha in LangChain
Lusha and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Lusha to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Lusha in LangChain
The Lusha MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Lusha for LangChain
Every tool call from LangChain to the Lusha MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can my AI automatically find the phone number for a LinkedIn profile?
Yes! Use the get_person_by_linkedin tool. Provide the LinkedIn URL, and your agent will respond with complete metadata for the record, including verified emails and direct phone numbers in seconds.
How do I find my Lusha API Key?
Log in to your Lusha account, navigate to Settings > API & Integrations, and you will find your unique secret token there.
Does it support bulk enrichment?
Yes, use the bulk_enrich_person tool to provide an array of contacts. The AI will process the batch and return enriched metadata for all entries in a single operation.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters