How to Use the Xiaoshouyi / Neocrm MCP in AutoGen

Debate complex decisions for Xiaoshouyi / Neocrm using AutoGen.

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Connect Xiaoshouyi / Neocrm MCP to AutoGen

Create your Vinkius account to connect Xiaoshouyi / Neocrm 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.

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Setup Xiaoshouyi / Neocrm with AutoGen

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Perplexity

Determine optimal lead handling strategies.

Instead of a single execution, you set up a debate. One agent can call `list_leads` and flag high-priority items. A second agent assesses the current opportunity status via `get_lead`. A third agent then debates whether creating an immediate follow-up task (`create_task`) is necessary before pursuing the lead.

Validate account setup integrity.

You can build a governance check. A validation agent reviews `list_accounts` against `list_users`. Another agent checks if all associated contacts are logged (`list_contacts`). The agents debate the completeness of the data, ensuring no gaps exist before marking an account active.

Complex pipeline planning and risk assessment.

Need to plan a major launch? Assign one agent to list all relevant opportunities (`list_opportunities`). Give another agent the job of checking required resources via `list_tasks`. The agents negotiate on timeline and resource allocation, converging on a final action plan for you.

Setup guide

Set up Xiaoshouyi / Neocrm 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 Xiaoshouyi / Neocrm 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="Xiaoshouyi / Neocrm_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Xiaoshouyi / Neocrm 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="Xiaoshouyi / Neocrm_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Xiaoshouyi / Neocrm 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 Xiaoshouyi / Neocrm. 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 Xiaoshouyi / Neocrm MCP in AutoGen

AutoGen is built for disagreement. You assign agents to specific tools—say, one agent handles `list_users` and another handles `create_lead`. They then debate the best way to combine that data.

It provides consensus. If you ask, 'Should we change this opportunity?', multiple agents—like a Risk Agent and an Execution Agent—will argue pros and cons until they reach a shared conclusion.

The tools cover the entire client relationship cycle: leads, contacts, accounts, opportunities, tasks, and organizational user records. The agents operate across all these data types.

Yes. You can set up a debate where one agent identifies missing tasks (`list_tasks`) and another proposes the best owner for those tasks, culminating in `create_task`.

The server manages sensitive user details, including contact PII. The multi-agent system must be carefully configured to ensure that the debate only uses data strictly necessary for the final decision.

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