Can I see exactly how my Lindy made a specific decision?

Yes. Use the `get_run_logs` tool with a specific Run ID. Your agent will retrieve the literal LLM reasoning loops and step-by-step validations, giving you full transparency into the autonomous agent's logic.

How do I trigger an autonomous task through a conversation?

The `trigger_lindy` tool allows you to start an asynchronous task run. You just need to provide the Lindy ID and a JSON payload defining the inputs for the task. Your agent will fire the job and return a Run ID for status tracking.

Can my agent list which third-party apps my Lindies are connected to?

Absolutely. Use the `list_integrations` tool to retrieve all active third-party app connections. Your agent will report which channels (like Slack, Gmail, or HubSpot) are securely connected to your workspace.

Lindy (Autonomous AI Employees) MCP Server for AutoGen 10 tools — connect in under 2 minutes

Name: Lindy (Autonomous AI Employees)
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools Framework

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

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 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="lindy_autonomous_ai_employees_agent",
            tools=tools,
            system_message=(
                "You help users with Lindy (Autonomous AI Employees). "
                "10 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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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 Lindy (Autonomous AI Employees) MCP Server

Connect your Lindy.ai account to any AI agent and take full control of your autonomous AI workforce and automated business processes through natural conversation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Lindy (Autonomous AI Employees) tools. Connect 10 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Lindy Orchestration — List all custom autonomous assistants (Lindies) built in your workspace and retrieve their core configurations and prompt instructions directly from your agent
Task Execution — Trigger specific Lindies to start asynchronous task runs using dynamic JSON payloads to automate complex business workflows
Reasoning Audit — Dump literal LLM reasoning logs for specific run loops to understand how your autonomous agents are making decisions and identifying steps
Run Monitoring — Track the state of active executions and manage lifecycle controls, including the ability to cancel runs stuck in context loops securely
Integration Visibility — Enumerate secure connections to third-party apps like Slack, Gmail, and CRM systems to manage your AI's reach across your software stack
Workspace Management — Navigate organizational boundaries and team structures to understand how Lindies are distributed across your company

The Lindy (Autonomous AI Employees) MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen 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 Lindy (Autonomous AI Employees) to AutoGen via MCP

Follow these steps to integrate the Lindy (Autonomous AI Employees) MCP Server with AutoGen.

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 10 tools from Lindy (Autonomous AI Employees) automatically

Why Use AutoGen with the Lindy (Autonomous AI Employees) MCP Server

AutoGen provides unique advantages when paired with Lindy (Autonomous AI Employees) through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Lindy (Autonomous AI Employees) tools to solve complex tasks

Role-based architecture lets you assign Lindy (Autonomous AI Employees) 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 Lindy (Autonomous AI Employees) tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Lindy (Autonomous AI Employees) tool responses in an isolated environment

Lindy (Autonomous AI Employees) + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Lindy (Autonomous AI Employees) MCP Server delivers measurable value.

Collaborative analysis: one agent queries Lindy (Autonomous AI Employees) while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Lindy (Autonomous AI Employees), a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Lindy (Autonomous AI Employees) data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Lindy (Autonomous AI Employees) responses in a sandboxed execution environment

Lindy (Autonomous AI Employees) MCP Tools for AutoGen (10)

These 10 tools become available when you connect Lindy (Autonomous AI Employees) to AutoGen via MCP:

cancel_run

Cancel a running execution dispatching hard stops interrupting trapped context loops

get_lindy

Get configuration mappings including standard tools and prompts for a specific Lindy

get_run

Get specific state for a Run blocking on Human input or External APIs

get_run_logs

Dump literal LLM reasoning logs isolating a specific run loop

list_integrations

List bounded third-party app connections securely connected (e.g Slack, Gmail)

list_lindies

List all custom autonomous AI Assistants (Lindies) built on the workspace

list_runs

List recent runs validating the full execution graph isolating active Lindy instances

list_triggers

List how autonomous AI agents are woken up (Cron, Webhook, API)

list_workspaces

List all explicit organizational boundaries structuring isolated Teams

trigger_lindy

Trigger a Lindy to start an asynchronous task run parsing a JSON payload

Example Prompts for Lindy (Autonomous AI Employees) in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Lindy (Autonomous AI Employees) immediately.

"List all active Lindies in my workspace"

"Show me the reasoning logs for the last run of 'Sales-Research-Lindy'"

"What triggers are currently configured for our autonomous agents?"

Troubleshooting Lindy (Autonomous AI Employees) MCP Server with AutoGen

Common issues when connecting Lindy (Autonomous AI Employees) to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

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

Lindy (Autonomous AI Employees) + AutoGen FAQ

Common questions about integrating Lindy (Autonomous AI Employees) 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 Lindy (Autonomous AI Employees) 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.