How does Findymail ensure the accuracy of the found emails?

Findymail uses a proprietary verification engine that checks the deliverability of B2B emails in real-time. By using the 'verify_email' tool, you can double-check any address to ensure your bounce rate stays below 1%.

Can I search for leads using natural language like 'Founders in San Francisco'?

Yes! The 'search_leads' tool uses the Intellimatch engine, allowing you to discover companies and contacts based on conversational queries. It's like having a lead researcher built into your AI agent.

What happens if a phone number or email cannot be found?

If Findymail cannot locate a verified contact, the tool will return a null or empty status. Findymail only charges credits for successful finds, ensuring you only pay for data you can actually use.

Findymail MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Findymail
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Findymail through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "findymail": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Findymail, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

About Findymail MCP Server

Connect your Findymail account to any AI agent and supercharge your sales prospecting and data enrichment workflows through the power of the Model Context Protocol (MCP). Findymail is designed for high-growth sales teams that need accurate, verified contact data without the manual grind of searching through LinkedIn or guessing email patterns.

LangChain's ecosystem of 500+ components combines seamlessly with Findymail 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.

What you can do

Precision Email Finding — Instantly retrieve verified B2B emails by providing a person's name and their company domain or name. No more guessing; get data that actually delivers.
Real-time Email Verification — Protect your sender reputation by verifying any email address before it hits your outreach sequence. Our verification tool checks for deliverability in seconds.
Direct Phone Discovery — Scale your cold calling efforts by fetching direct phone numbers directly from LinkedIn profiles using our specialized phone finder tool.
Deep Company Enrichment — Transform a simple domain or LinkedIn URL into a full company profile, including industry data, size, and social identifiers.
Intellimatch Lead Generation — Use natural language to discover new leads. Simply ask your agent to 'Find SaaS founders in the US' or 'Get me marketing heads in London', and let Findymail do the heavy lifting.
List & Contact Management — Organically manage your prospecting lists and retrieve specific contact details to keep your CRM updated and your outreach personalized.
Credit Monitoring — Keep a pulse on your API usage with built-in tools to check your remaining credits and usage summaries directly from your AI conversation.

The Findymail MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Findymail to LangChain via MCP

Follow these steps to integrate the Findymail MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Findymail via MCP

Why Use LangChain with the Findymail MCP Server

LangChain provides unique advantages when paired with Findymail through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Findymail MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Findymail queries for multi-turn workflows

Findymail + LangChain Use Cases

Practical scenarios where LangChain combined with the Findymail MCP Server delivers measurable value.

RAG with live data: combine Findymail tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Findymail, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Findymail tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Findymail tool call, measure latency, and optimize your agent's performance

Findymail MCP Tools for LangChain (12)

These 12 tools become available when you connect Findymail to LangChain via MCP:

create_contact_list

Create a new contact list

enrich_company

Enrich company data

find_email

Find a verified email address

find_phone

Find direct phone numbers

get_contact

Get contact details

get_credits

Check credit balance

get_credits_summary

Get credits usage summary

get_lead_search_data

Get lead search results

get_lead_search_status

Check lead search status

list_contact_lists

List all contact lists

search_leads

Find companies and contacts

verify_email

Verify an email address

Example Prompts for Findymail in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Findymail immediately.

"Find the verified email for Satya Nadella at microsoft.com"

"Enrich company data for the domain 'vinkius.com'"

"Search for 'marketing agency owners in New York' using Intellimatch."

Troubleshooting Findymail MCP Server with LangChain

Common issues when connecting Findymail to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Findymail + LangChain FAQ

Common questions about integrating Findymail MCP Server with LangChain.

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.