How do I get an API Token for Fountain?

You can find or generate your API token in your Fountain dashboard under Company Settings > Developer Settings.

Does Fountain support bulk actions?

Yes, the Fountain API is designed for scale. While this MCP server focuses on management and retrieval, bulk advance and transitions are supported by the core platform.

Can I see interview schedules via the agent?

Yes, the 'list_interview_sessions' tool allows you to retrieve all scheduled and past interview sessions directly from your account.

Is worker data accessible after hire?

Yes, you can use the 'list_workers' tool to access profiles of individuals who have successfully transitioned to 'hired' status.

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

Name: Fountain
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 Fountain 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({
        "fountain": {
            "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 Fountain, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Fountain MCP Server

Connect your Fountain account to any AI agent to automate your high-volume hiring and applicant lifecycle management through the Model Context Protocol (MCP). Fountain is designed specifically for frontline workforce management, allowing you to streamline every stage from sourcing to onboarding. This MCP server enables you to manage your applicant funnels, track hiring progress, and oversee worker profiles directly through natural conversation.

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

Key Features

Applicant Oversight — List all applicants, search by email or funnel, and fetch detailed profiles including transition history.
Funnel & Stage Management — Access and list your hiring funnels and specific stages to understand your pipeline health.
Hiring Goal Tracking — Monitor your progress against specific hiring targets and performance metrics.
Opening Management — List all active job openings and fetch detailed metadata for specific positions.
Interview Coordination — List and oversee scheduled interview sessions across your organization.
Worker Profiles — Access metadata for individuals who have successfully completed the hiring process.
Sourcing Insights — Monitor published job posts across various channels to optimize your recruitment reach.

The Fountain 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 Fountain to LangChain via MCP

Follow these steps to integrate the Fountain 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 Fountain via MCP

Why Use LangChain with the Fountain MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Fountain 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 Fountain queries for multi-turn workflows

Fountain + LangChain Use Cases

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

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

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

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

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

Fountain MCP Tools for LangChain (12)

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

get_account_details

Get organization attributes

get_applicant

Get applicant details

get_opening_details

Get opening metadata

list_applicant_notes

Get applicant discussion

list_applicants

List job applicants

list_funnel_stages

List stages in a funnel

list_funnels

List hiring funnels

list_hiring_goals

List hiring targets

list_interview_sessions

List scheduled interviews

list_job_posts

List published job posts

list_openings

List active job openings

list_workers

List hired workers

Example Prompts for Fountain in LangChain

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

"List all active job openings in Fountain."

"Show me the last 10 applicants for the 'Delivery' funnel."

"Get the hiring goals summary for this quarter."

Troubleshooting Fountain MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Fountain + LangChain FAQ

Common questions about integrating Fountain 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.