How to Use the Birdeye MCP in AutoGen

Q: How do I register Birdeye tools with AutoGen?

Use the mcpservertools helper from autogen-extmcp to fetch the tools. You then pass this tool list directly to your AssistantAgent constructor to give it access to functions like listcontacts.

Q: How do AutoGen agents handle Birdeye business locations?

The agents use listlocations to identify which branch a customer visited. A coordinator agent then passes the correct location ID to the agent responsible for running checkincustomer.

Let AutoGen agents debate and coordinate review replies and customer check-ins using Birdeye tools.

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Connect Birdeye MCP to AutoGen

Create your Vinkius account to connect Birdeye 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 Birdeye with AutoGen

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Coordinate Birdeye review replies with AutoGen agents

The `reply_to_review` tool allows your AutoGen agents to post responses to Birdeye customer feedback. Before posting to Birdeye, an AutoGen writer agent drafts the reply and a quality agent reviews it. Once both AutoGen agents agree, the writer agent calls the tool to publish the Birdeye response. This AutoGen group-chat approach eliminates poorly written Birdeye responses.

Automate Birdeye customer check-ins via multi-agent consensus

The `checkin_customer` tool triggers Birdeye review requests when an AutoGen task completes. An AutoGen routing agent identifies the transaction, while a compliance agent checks Birdeye contact history. They negotiate the best time to send the Birdeye request, invoking the tool only after AutoGen consensus. This prevents spamming your Birdeye contact list and protects your response rates.

Analyze business reputation using this MCP Server

The `get_review_summary` tool retrieves Birdeye review counts for your AutoGen agents to analyze. An AutoGen analyst agent reads the Birdeye summary, while a strategy agent suggests improvements. The AutoGen agents use `list_reviews` to drill down into low-score Birdeye reviews and debate the root cause. This turns Birdeye reputation management into a collaborative AutoGen analysis.

Setup guide

Set up Birdeye 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 Birdeye 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="Birdeye_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="Birdeye_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Birdeye 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 Birdeye. 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 Birdeye MCP in AutoGen

Use the `mcp_server_tools` helper from `autogen-ext[mcp]` to fetch the tools. You then pass this tool list directly to your `AssistantAgent` constructor to give it access to functions like `list_contacts`.

Yes, you can set up a multi-agent round-robin where one agent retrieves reviews using `list_reviews` and another uses `reply_to_review` to respond. They debate the draft response in the chat before executing the call.

The agents use `list_locations` to identify which branch a customer visited. A coordinator agent then passes the correct location ID to the agent responsible for running `checkin_customer`.

Yes, this MCP Server supports both stdio and Streamable HTTP transports. You can configure it easily using the `StreamableHttpServerParams` class within your AutoGen setup.

All customer contact records and business details are handled within secure, ephemeral sandboxes. Vinkius does not store or log the customer names, phone numbers, or email addresses processed during tool execution.

Use it with your favorite AI tools

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