How to Use the Emplifi MCP in AutoGen

Debate social strategy with the Emplifi MCP Server and AutoGen's multi-agent conversation framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Emplifi MCP to AutoGen

Create your Vinkius account to connect Emplifi 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.

GDPR Free for Subscribers

Setup Emplifi with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Negotiate care routing with multiple agents

Deploy a team of agents where one monitors `list_care_automation_rules` and another evaluates team capacity via `list_organization_team_members`. They debate the best routing strategy for high-volume periods. This isn't a single prompt response. The agents check the feasibility of your rules against current staffing levels, ensuring the final decision is realistic and operational.

Challenge metrics with performance agents

Have your performance agent pull numbers via `get_influencer_performance_stats` while a critic agent questions the validity of those trends. They reconcile the data before presenting you with a summary. It prevents jumping to conclusions based on single data points. The agents work through the metrics, ensuring that the insights derived from your social profiles are balanced and accurate.

Run automated health audits as a team

Task your administrative agent with performing a `quick_cx_health_audit`. The results are then shared with your support agents, who discuss how to address any flagged issues in your care workflows. It forces a collaborative review of your support health. By distributing the audit results to specialists, you ensure that the findings are acted upon by the right team members.

Setup guide

Set up Emplifi 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 Emplifi 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="Emplifi_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Emplifi 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="Emplifi_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Emplifi 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 Emplifi. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Emplifi now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Emplifi MCP in AutoGen

You pass the Emplifi tool list to your AssistantAgent constructor. The MCP adapter handles the schema mapping, allowing all agents in your conversation group to invoke the server functions.

Yes, that's the point. You set up a critic agent to challenge the findings of your data-fetcher agent, leading to a more rigorous interpretation of your social listening dashboards.

It does. Each agent in the AutoGen group calls the server independently, allowing for parallel data gathering from your social profiles.

You define which tools each agent can access in the constructor. You might restrict the 'critic' agent to only reading metrics, while the 'manager' agent has full control over automation rules.

The server manages the handshake using your endpoint token. Within AutoGen, the tools are pre-authenticated, so your agents focus on the conversation logic rather than managing access to your social data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript