HiFlow MCP Server for AutoGenGive AutoGen instant access to 12 tools to Create Customer, Get Activity, Get Customer, and more

Name: HiFlow
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add HiFlow as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

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The HiFlow MCP Server for AutoGen is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="hiflow_agent",
            tools=tools,
            system_message=(
                "You help users with HiFlow. "
                "12 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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* 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.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use HiFlow tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

The HiFlow MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen 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 AutoGen

When AutoGen 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

Create customer on HiFlow

Create a new customer

get

Get activity on HiFlow

Retrieve activity dashboard information

get

Get customer on HiFlow

Retrieve details for a specific customer

get

Get estimate on HiFlow

Retrieve details for a specific estimate

get

Get invoice on HiFlow

Retrieve details for a specific invoice

get

Get job on HiFlow

Retrieve details for a specific job

get

Get me on HiFlow

Retrieve information about the current user

list

List customers on HiFlow

List all customers

list

List estimates on HiFlow

List all estimates (quotes)

list

List invoices on HiFlow

List all invoices

list

List jobs on HiFlow

List all jobs/projects

list

List timesheets on HiFlow

List all timesheet entries

Connect HiFlow to AutoGen via MCP

Follow these steps to wire HiFlow into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 12 tools from HiFlow automatically

Why Use AutoGen with the HiFlow MCP Server

AutoGen provides unique advantages when paired with HiFlow through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use HiFlow tools to solve complex tasks

Role-based architecture lets you assign HiFlow tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive HiFlow tool calls

Code execution sandbox: AutoGen agents can write and run code that processes HiFlow tool responses in an isolated environment

HiFlow + AutoGen Use Cases

Practical scenarios where AutoGen combined with the HiFlow MCP Server delivers measurable value.

Collaborative analysis: one agent queries HiFlow while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from HiFlow, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using HiFlow data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process HiFlow responses in a sandboxed execution environment

Example Prompts for HiFlow in AutoGen

Ready-to-use prompts you can give your AutoGen 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 AutoGen

Common issues when connecting HiFlow to AutoGen through Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

HiFlow + AutoGen FAQ

Common questions about integrating HiFlow MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call HiFlow tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.