How to Use the HeyReach MCP in AutoGen
Deploy multi-agent debates to execute LinkedIn outreach campaigns via AutoGen and this MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect HeyReach MCP to AutoGen
Create your Vinkius account to connect HeyReach 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.
Consensus-Driven Lead Importing
The HeyReach MCP Server integrates with AutoGen's multi-agent conversation framework to let specialized agents debate and qualify leads. Once they agree on a list, the execution agent calls `add_leads_to_campaign` to push them into your outreach queue. This multi-agent verification in AutoGen prevents bad leads from ruining your sender reputation. It's a solid way to check the prospect's profile using `get_lead_details` before signing off on the import.
Multi-Agent Inbox Moderation via MCP Server
This MCP Server allows specialized AutoGen agents to manage your LinkedIn inbox cooperatively. A monitoring agent calls `list_conversations` to flag unread replies, while a draft agent writes responses, and a manager agent reviews them before calling `send_linkedin_message`. This collaborative AutoGen workflow ensures high-quality responses. Because this server exposes direct message tools, your agents can coordinate complex negotiations on LinkedIn without human intervention.
Automated Campaign Safety Rails
Protect your LinkedIn profiles from restrictions by using this MCP Server to set up AutoGen safety rails. One AutoGen agent monitors sending volumes via `list_linkedin_accounts`, while another checks campaign statuses using `list_campaigns` to ensure you stay under daily limits. If an account gets close to its safety limit, the AutoGen safety agent immediately calls `pause_campaign` to halt activity. They'll negotiate when it's safe to run `resume_campaign` based on account health.
Set up HeyReach 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 HeyReach 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="HeyReach_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent HeyReach 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="HeyReach_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent HeyReach 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 HeyReach. 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 HeyReach MCP in AutoGen
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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