HrFlow.ai MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect HrFlow.ai through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"hrflowai": {
"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 HrFlow.ai, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 HrFlow.ai MCP Server
Empower your AI agents with HrFlow.ai's advanced talent acquisition capabilities. This MCP server allows you to parse resumes, search profiles and jobs with semantic filters, score candidates against job descriptions, and ask natural language questions about profiles. Ideal for automating recruitment workflows with AI-driven insights.
LangChain's ecosystem of 500+ components combines seamlessly with HrFlow.ai through native MCP adapters. Connect 10 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.
The HrFlow.ai MCP Server exposes 10 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 HrFlow.ai to LangChain via MCP
Follow these steps to integrate the HrFlow.ai 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 10 tools from HrFlow.ai via MCP
Why Use LangChain with the HrFlow.ai MCP Server
LangChain provides unique advantages when paired with HrFlow.ai through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine HrFlow.ai 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 HrFlow.ai queries for multi-turn workflows
HrFlow.ai + LangChain Use Cases
Practical scenarios where LangChain combined with the HrFlow.ai MCP Server delivers measurable value.
RAG with live data: combine HrFlow.ai tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query HrFlow.ai, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain HrFlow.ai tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every HrFlow.ai tool call, measure latency, and optimize your agent's performance
HrFlow.ai MCP Tools for LangChain (10)
These 10 tools become available when you connect HrFlow.ai to LangChain via MCP:
ask_profile
Asks a natural language question about a specific profile
list_boards
Lists job boards
list_jobs
Lists jobs stored in HrFlow boards
list_profiles
Lists candidate profiles stored in HrFlow
list_sources
Lists profile sources
parse_profile
Parses a resume file into a structured profile
score_profiles
Scores candidate profiles against a specific job
search_jobs
Searches for jobs with semantic filters
search_profiles
Searches for profiles with semantic filters
unfold_profile
Analyzes and unfolds the career path of a profile
Example Prompts for HrFlow.ai in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with HrFlow.ai immediately.
"List the last 5 profiles added to my HrFlow source."
"Ask profile key 'abc-123' if they have experience with Kubernetes."
"Find jobs that match candidate 'john-doe-key'."
Troubleshooting HrFlow.ai MCP Server with LangChain
Common issues when connecting HrFlow.ai to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersHrFlow.ai + LangChain FAQ
Common questions about integrating HrFlow.ai MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect HrFlow.ai with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect HrFlow.ai to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.