How to Use the Yousign MCP in AutoGen

Q: How do I check my quotas when using Yousign with AutoGen?

The agent uses getconsumption. If the performance agent flags that quota is low, it stops the pipeline and reports back to you immediately.

Q: Can multiple agents collaboratively start a signing workflow for Yousign?

Sure thing. One agent creates the initial draft using createrequest, and another agent then debates whether or not they should proceed with activation via activaterequest.

Q: If I need to list all past jobs for Yousign with AutoGen, what do I use?

Use listrequests. The agents can debate the best way to filter this massive output, ensuring only relevant job statuses are passed forward.

Q: How do I check documents for Yousign with AutoGen?

You run listdocuments and feed that output into the agents' discussion. They then debate if the document count is sufficient to proceed or if more context is needed.

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Perplexity

Debate the next steps for a signature job.

Start by calling `get_request` to gather all details about an active signing process. Multiple agents can then debate whether the status is 'complete' or if more action is needed. If consensus requires adding people, one agent can call `add_signer`, while another verifies that the ID exists first.

Negotiate document inclusion.

A security agent might challenge a plan because it relies on unverified documents. To settle this, your system uses `list_documents` to present all available attachments for review. This forces the agents into deliberation: 'Should we proceed with these listed files or wait for others?'

Manage and cancel processes by consensus.

If multiple agents disagree on whether a request should continue, you can use `cancel_request`. The debate itself leads to the decision that triggers this tool. Alternatively, agents can first run `list_requests` to establish context before agreeing on which job needs attention.

Setup guide

Set up Yousign 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 Yousign 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="Yousign_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Yousign data")
print(result.messages[-1].content)

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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="Yousign_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Yousign data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Yousign. 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 Yousign MCP in AutoGen

The agent uses `get_consumption`. If the performance agent flags that quota is low, it stops the pipeline and reports back to you immediately.

Sure thing. One agent creates the initial draft using `create_request`, and another agent then debates whether or not they should proceed with activation via `activate_request`.

Use `list_requests`. The agents can debate the best way to filter this massive output, ensuring only relevant job statuses are passed forward.

The server touches API consumption and quota details. This usage metadata is key for the agent to debate resource availability before proceeding with any action.

You run `list_documents` and feed that output into the agents' discussion. They then debate if the document count is sufficient to proceed or if more context is needed.

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