How to Use the Salespanel MCP in AutoGen
Let your AutoGen agents debate and qualify Salespanel leads. Build a team of AI specialists who find, vet, and prioritize your sales pipeline.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Salespanel MCP to AutoGen
Create your Vinkius account to connect Salespanel to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Let Your Agents Debate Leads
With AutoGen, you don't have one agent; you have a team. Create a 'Scout' agent that uses `list_anonymous_visitors` and `list_activity_feeds` to find potential leads. It then passes its findings to another agent for review. Then, a 'Profiler' agent can take over. It uses `get_visitor` and `get_company` to enrich the data and presents a summary. This multi-agent conversation ensures a lead is properly vetted from multiple angles before it ever gets to a human.
Build a Sales Ops Team in AutoGen
You can design agents with specific jobs. For example, a 'Compliance' agent's only job is to check a contact against `list_lead_segments`. If a lead is in the 'Existing Customer' segment, it vetoes any outreach. Meanwhile, a 'Growth' agent might be arguing to engage with every new lead from `list_contacts`. AutoGen lets them debate based on the data from this MCP server. The final decision is a consensus, not a single-threaded command. It's a more robust way to automate decisions.
Simulate Your Sales Workflow
This MCP server gives your agents the raw material to work with. They can pull account lists with `list_accounts` and `list_companies`, see who's active with `list_engagement_events`, and get contact details with `get_contact_details`. The power of AutoGen is modeling the handoffs. One agent finds the lead, another enriches it, a third one checks for conflicts, and a final 'Notifier' agent summarizes the result for the sales team. You're building an automated assembly line for lead intelligence.
Set up Salespanel 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 Salespanel 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="Salespanel_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Salespanel 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="Salespanel_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Salespanel 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 Salespanel. 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 Salespanel MCP in AutoGen
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