How to Use the meetergo MCP in AutoGen
Let your AutoGen agents debate routing options and coordinate meetergo schedules through multi-agent consensus.
Works with every AI agent you already use
…and any MCP-compatible client
Connect meetergo MCP to AutoGen
Create your Vinkius account to connect meetergo 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.
Resolve routing disputes with AutoGen agents
This meetergo MCP Server exposes `list_users` and `get_availability` to let your AutoGen agents negotiate the best rep for an incoming enterprise lead. A routing agent proposes a rep, while a QA agent checks their current calendar load before agreeing. This multi-agent debate ensures that high-value leads are not routed to reps who are already overbooked. The agents deliberate using live calendar data, converging on a consensus before executing any actions.
Automate booking validation via agent consensus
Use `create_booking` to let your AutoGen execution agent finalize meetings once the routing agents have reached an agreement. The framework coordinates the entire process, verifying the booking details against company policies. Before the booking is finalized, a compliance agent can call `get_meeting_type` to verify that the selected template matches the prospect's contract size. This prevents reps from accidentally scheduling incorrect meeting formats.
Coordinate schedule updates across multiple agents
The `cancel_booking` tool allows your AutoGen agents to automatically reschedule conflicts when a prospect requests a change. A coordinator agent detects the reschedule request, while a booking agent finds a new slot. The agents work together to verify availability using `get_availability` before making the final change. This eliminates manual calendar management, keeping your sales team's schedules organized without human intervention.
Set up meetergo 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes meetergo tools and returns structured results.
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="meetergo_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent meetergo data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="meetergo_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent meetergo data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by meetergo. 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 meetergo MCP in AutoGen
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