How to Use the Mokaform MCP in AutoGen

Q: Can multiple AutoGen agents use Mokaform tools simultaneously?

Yes, different agents can call getform and listresponses at the same time. The Vinkius infrastructure handles the concurrent requests safely within its sandbox.

Q: How do AutoGen agents handle schema validation errors?

If an agent inputs invalid parameters to createform, the server returns a detailed schema error. The agents then debate the error and correct the payload before retrying.

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Connect Mokaform MCP to AutoGen

Create your Vinkius account to connect Mokaform 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 Mokaform with AutoGen

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Design forms through multi-agent consensus

The `create_form` tool allows your AutoGen design agent to build new forms after negotiating the layout with a review agent. One agent drafts the questions, while the other critiques the branching logic before executing the creation. This collaborative process ensures your survey design remains logical and clean. Once they agree, the active agent runs `update_form` to apply the finalized schema to your workspace.

Analyze responses using AutoGen MCP Server tools

The `get_response` tool feeds specific submission data into an AutoGen debate loop. A sentiment analysis agent and a customer success agent analyze the feedback to determine the next action. If the agents identify a critical bug report, they coordinate to run `list_responses` and check if other users face the same issue. They compile a clean summary for your engineering team without human intervention.

Manage workspace lifecycles autonomously

The `list_workspaces` tool lets your agent fleet audit your entire organizational structure. The coordinator agent assigns specific workspaces to sub-agents for maintenance tasks. When an agent flags spam submissions, it initiates a vote to trigger `delete_response` on those specific records. This keeps your workspace clean and free of junk data automatically.

Setup guide

Set up Mokaform 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 Mokaform 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="Mokaform_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Mokaform 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="Mokaform_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Mokaform 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 Mokaform. 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 Mokaform MCP in AutoGen

You use the MCP tool adapter to convert the Vinkius HTTP server parameters. Then, you pass the adapted tools list directly to your AssistantAgent constructor.

Yes, different agents can call `get_form` and `list_responses` at the same time. The Vinkius infrastructure handles the concurrent requests safely within its sandbox.

If an agent inputs invalid parameters to `create_form`, the server returns a detailed schema error. The agents then debate the error and correct the payload before retrying.

Yes, the adapter supports both stdio and Streamable HTTP transports. Vinkius manages the connection details so your agents can focus on executing the tools.

Vinkius routes all tool executions through isolated V8 sandboxes with zero-trust policies. Your workspace metadata and API tokens are never exposed to other agents or external logs.

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