How to Use the Lusha MCP in AutoGen

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Connect Lusha MCP to AutoGen

Create your Vinkius account to connect Lusha to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Lusha with AutoGen

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Consensus-driven prospecting with AutoGen

Assign one agent to search with `prospect_new_leads` and another to verify the results. They discuss the quality of the leads, ensuring only high-value targets move forward. This removes the guesswork from your outbound strategy. The agents negotiate based on the data returned, pushing for the best possible results before finalizing a lead list.

Automated verification of contact info

Use a specialized agent to challenge the data quality of incoming records. It can call `get_person_by_email` to cross-reference details, ensuring your outbound messages reach the right inbox. This keeps your domain reputation intact. By having an agent double-check the findings, you catch bad data before it hits your mailing list.

Monitor account limits across agents

Create a manager agent that tracks your API consumption. It periodically calls `get_credit_balance` to ensure your team of agents doesn't exceed your quarterly budget. This provides a safety net for your operations. If credits run low, the manager agent can halt the prospecting process and alert you to top up before the next cycle.

Setup guide

Set up Lusha MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Lusha tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Lusha_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Lusha data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Lusha_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Lusha data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Lusha. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Lusha MCP in AutoGen

Yes, you can register the tools with any number of agents in your conversation group. They will share access to the same server endpoint.

Agents use their internal reasoning to determine when data is needed. If the conversation requires a lead's contact info, the agent will trigger the tool automatically.

You can define which tools are available to specific agents in the constructor. This ensures only authorized agents can perform actions like bulk enrichment.

The agents share the tool interface, but session persistence depends on your server configuration. Use a persistent session to maintain state across long-running debates.

Your contact information is only used within the scope of the agent conversation. The server processes the request and returns the data directly to the agent without external logging.

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