HiFlow MCP Server for LangChainGive LangChain instant access to 12 tools to Create Customer, Get Activity, Get Customer, and more
LangChain is the leading Python framework for composable LLM applications. Connect HiFlow 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 for LangChain
The HiFlow MCP Server for LangChain is a standout in the Productivity category — giving your AI agent 12 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({
"hiflow": {
"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 HiFlow, 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 HiFlow MCP Server
The HiFlow MCP server bridges your AI agent with your enterprise workflows. Trigger processes, approve pending steps, and query real-time process states through a seamless conversational interface.
LangChain's ecosystem of 500+ components combines seamlessly with HiFlow 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.
The HiFlow MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 HiFlow tools available for LangChain
When LangChain connects to HiFlow through Vinkius, your AI agent gets direct access to every tool listed below — spanning workflow-automation, bpm, process-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Create customer on HiFlow
Create a new customer
Get activity on HiFlow
Retrieve activity dashboard information
Get customer on HiFlow
Retrieve details for a specific customer
Get estimate on HiFlow
Retrieve details for a specific estimate
Get invoice on HiFlow
Retrieve details for a specific invoice
Get job on HiFlow
Retrieve details for a specific job
Get me on HiFlow
Retrieve information about the current user
List customers on HiFlow
List all customers
List estimates on HiFlow
List all estimates (quotes)
List invoices on HiFlow
List all invoices
List jobs on HiFlow
List all jobs/projects
List timesheets on HiFlow
List all timesheet entries
Connect HiFlow to LangChain via MCP
Follow these steps to wire HiFlow into LangChain. The entire setup takes under two minutes — your credentials stay safe behind 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 HiFlow MCP Server
LangChain provides unique advantages when paired with HiFlow through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine HiFlow 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 HiFlow queries for multi-turn workflows
HiFlow + LangChain Use Cases
Practical scenarios where LangChain combined with the HiFlow MCP Server delivers measurable value.
RAG with live data: combine HiFlow tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query HiFlow, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain HiFlow tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every HiFlow tool call, measure latency, and optimize your agent's performance
Example Prompts for HiFlow in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with HiFlow immediately.
"List my pending approvals."
"Start the 'Employee Onboarding' process for John Doe."
"Approve task ID 9481."
Troubleshooting HiFlow MCP Server with LangChain
Common issues when connecting HiFlow to LangChain through Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersHiFlow + LangChain FAQ
Common questions about integrating HiFlow 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?
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