HRBlade MCP Server for LangChainGive LangChain instant access to 6 tools to Create Interview, Get Candidate Details, List Candidates, and more
LangChain is the leading Python framework for composable LLM applications. Connect HRBlade 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 App Connector for LangChain
The HRBlade app connector for LangChain is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"hrblade": {
"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 HRBlade, 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 HRBlade MCP Server
Connect your HRBlade account to any AI agent and manage asynchronous video interviews through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with HRBlade through native MCP adapters. Connect 6 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
- Interview Templates — List all interview templates and create new ones with custom questions, time limits, and instructions
- Candidate Invitations — Send video interview invitations to candidates by email with personalized details
- Candidate Management — Browse all candidates in your pipeline and inspect individual profiles with status
- Response Review — List all submitted video responses to review candidate answers and evaluate performance
The HRBlade MCP Server exposes 6 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.
All 6 HRBlade tools available for LangChain
When LangChain connects to HRBlade through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-interviewing, candidate-screening, hiring-pipeline, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Pass data as a JSON string. Create a new interview template
Get specific candidate details
List all recruiting candidates
List all candidate video responses
List all interview templates
Pass data as a JSON string. Send an invitation to a candidate
Connect HRBlade to LangChain via MCP
Follow these steps to wire HRBlade into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the HRBlade MCP Server
LangChain provides unique advantages when paired with HRBlade through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine HRBlade 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 HRBlade queries for multi-turn workflows
HRBlade + LangChain Use Cases
Practical scenarios where LangChain combined with the HRBlade MCP Server delivers measurable value.
RAG with live data: combine HRBlade tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query HRBlade, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain HRBlade tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every HRBlade tool call, measure latency, and optimize your agent's performance
Example Prompts for HRBlade in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with HRBlade immediately.
"Create a 'Senior Developer' interview with 3 technical questions and send it to 2 candidates."
"Show all candidates in my pipeline and the latest video responses."
"List all interview templates and show which ones have pending responses to review."
Troubleshooting HRBlade MCP Server with LangChain
Common issues when connecting HRBlade to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersHRBlade + LangChain FAQ
Common questions about integrating HRBlade 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.