How to Use the Mention MCP in AutoGen
Let your AutoGen agents debate and analyze social media trends using real-time data from Mention.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Mention MCP to AutoGen
Create your Vinkius account to connect Mention 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.
Run multi-agent Mention audits via MCP Server
This Mention MCP Server provides the raw social data your specialized AutoGen agents need to debate brand reputation. An AutoGen sentiment analyst agent pulls posts using `list_mentions`, while an AutoGen PR strategist agent evaluates the business impact. They negotiate the best Mention response strategy inside AutoGen based on hard numbers. This collaborative AutoGen approach ensures your Mention brand response is balanced and context-aware.
Coordinate AutoGen crisis alerts using Mention
Your automated AutoGen response team uses `get_alert_statistics` to monitor for sudden Mention volume spikes. Once a Mention spike is detected, an AutoGen coordinator agent initiates a debate among your sub-agents to determine if a crisis protocol is necessary. The AutoGen agents verify the threat by calling `get_mention_details` on the loudest Mention posts. They only trigger external notifications once AutoGen reaches a consensus on the severity of the Mention alert.
Delegate Mention research to specialized AutoGen agents
You assign specific Mention research tasks to individual agents within your AutoGen group. One AutoGen agent manages the monitoring setup using `list_alerts`, while another focuses on searching for specific competitive keywords via `search_mentions`. This division of labor keeps your AutoGen workflows for Mention monitoring fast and organized. Each AutoGen agent calls only the specific Mention tools required for its role, minimizing token usage and API overhead.
Set up Mention 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 Mention 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="Mention_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Mention 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="Mention_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Mention 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 Mention. 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 Mention MCP in AutoGen
Use it with your favorite AI tools
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