How to Use the Helpshift MCP in AutoGen
Deploy multi-agent AutoGen teams to debate, triage, and resolve Helpshift support issues with full consensus.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Helpshift MCP to AutoGen
Create your Vinkius account to connect Helpshift 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.
Multi-Agent Triage with AutoGen and MCP
Complex support cases shouldn't rely on a single agent's judgment. In this setup, a triage agent uses `list_issues` to grab incoming tickets, while a security agent reviews the history. They debate the issue's severity before taking action. Once they reach an agreement, the coordinator agent uses `update_issue_status` to assign or close the ticket. This collaborative approach ensures that high-priority security concerns are never misclassified as simple billing questions.
Collaborative Bulk Operations
Running bulk updates on customer profiles is risky if done blindly. This MCP Server solves this by splitting the work across your AutoGen team. One agent drafts the profile changes using `bulk_user_action`, while an audit agent checks the queue status using `get_bulk_task_status`. If the audit agent detects an error rate above your threshold, it instructs the team to pause. This constant feedback loop between specialized agents prevents corrupt data from spreading across your entire customer database.
Draft Responses with Multi-Agent Review
Writing customer-facing responses requires a balance of accuracy and tone. A writer agent uses `list_faqs` to find the correct technical answer for an issue. It drafts a message, which a reviewer agent then checks against past customer interactions retrieved via `get_issue_details`. After the review agent approves the draft, the writer agent calls `add_issue_message` to send the response. This multi-step validation ensures your customers receive clear, professional, and accurate support without human editors.
Set up Helpshift 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 Helpshift 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="Helpshift_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Helpshift 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="Helpshift_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Helpshift 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 Helpshift. 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 Helpshift MCP in AutoGen
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