How to Use the Funil de Vendas MCP in AutoGen
Assemble teams of AutoGen agents that talk, debate, and manage your Funil de Vendas CRM data together.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Funil de Vendas MCP to AutoGen
Create your Vinkius account to connect Funil de Vendas 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.
Let agents debate the next move
This is about consensus, not commands. One agent, the 'Analyst', can use `list_crm_opportunities` to flag a deal that's stalled. It passes this to a 'Strategist' agent, which then checks `list_crm_activities` to see the last contact date. The agents converse. The Strategist might suggest a follow-up, and the Analyst can then execute `create_crm_activity`. You're building a system where multiple perspectives lead to a better decision.
Validate new leads through conversation
Set up a simple assembly line for new leads. A 'Scout' agent might propose a new opportunity using `create_new_deal_lead`. But before it executes, a 'Validator' agent checks the data against `list_crm_custom_fields` for completeness and `list_lead_origins` to prevent duplicates. If the Validator finds a problem, it tells the Scout. They go back and forth until the data is clean. This prevents bad data from ever entering your CRM, all through automated agent conversation.
Equip your AutoGen agents for CRM tasks
The `autogen-ext[mcp]` package makes it easy. Use `mcp_server_tools` to get all the Funil de Vendas functions and pass them to your `AssistantAgent`. The `McpToolAdapter` handles the tricky parts, so your agents can just call `update_crm_activity` or `list_sales_vendors` as needed. This MCP Server provides the connection and the tools. You focus on designing the agent conversations and roles. Let them figure out how to work your sales pipeline.
Set up Funil de Vendas 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 Funil de Vendas 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="Funil de Vendas_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Funil de Vendas 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="Funil de Vendas_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Funil de Vendas 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 Funil de Vendas. 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 Funil de Vendas MCP in AutoGen
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