How to Use the Yousign MCP in Pydantic AI

Q: How do I get the signature status using Yousign and Pydantic AI?

Call getsignaturerequest. Since this is a type-safe framework, you'll receive a validated object showing the current state. This prevents your agent from misinterpreting ambiguous API responses.

Q: What happens when I add documents using Yousign and Pydantic AI?

When adddocumenttorequest runs, it expects a specific structure for the PDF and metadata. If the data doesn't match your defined schema, the agent fails with an explicit validation error, protecting your workflow integrity.

Q: Can I list all my signing requests using Yousign and Pydantic AI?

Yes, use listsignaturerequests. The response data is strictly validated against a Pydantic model, so you know exactly what fields to expect when managing your request list.

Q: How do I ensure the signer identity is correct with Yousign and Pydantic AI?

You define signers using addsignertorequest. Because of the type-safe validation, you know that the required parameters for each signer are present and structured correctly before the request moves forward.

Validate secure document signing workflows with Pydantic AI's type safety.

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Setup Yousign with Pydantic AI

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Handling Signature Request State

When you start a process, the agent calls `create_signature_request` and expects a strictly typed response detailing the initial state. If you need to check on it later, running `get_signature_request` returns data that is immediately validated against your Pydantic schema. This means if the API sends unexpected field names or types, your agent fails loudly, preventing silent corruption of critical contract data.

Document and Contact Management

To manage documents, you use `add_document_to_request` to pass both the file and its metadata, ensuring these components are structured correctly. Similarly, when adding a user via `create_yousign_contact`, the data is validated right away. This focus on type safety guarantees that every piece of information—from the address book to the document payload—is correct before proceeding.

Workflow Control and Auditing

If you need proof, `get_audit_trail_link` provides a verifiable link. If the workflow gets messy, calling `cancel_ongoing_request` cleanly terminates it. The agent also supports listing all documents via `list_signature_requests` to keep your records accurate. This validation layer ensures that even destructive actions like running `delete_signature_request` are handled predictably.

Setup guide

Set up Yousign MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "yousign-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Yousign tools.",
)

result = await agent.run("List recent Yousign transactions")
print(result.output)

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Common questions about Yousign MCP in Pydantic AI

Call `get_signature_request`. Since this is a type-safe framework, you'll receive a validated object showing the current state. This prevents your agent from misinterpreting ambiguous API responses.

When `add_document_to_request` runs, it expects a specific structure for the PDF and metadata. If the data doesn't match your defined schema, the agent fails with an explicit validation error, protecting your workflow integrity.

Yes, use `list_signature_requests`. The response data is strictly validated against a Pydantic model, so you know exactly what fields to expect when managing your request list.

This MCP Server handles contact information and document metadata. The specific data types validated are `yousign_contacts` (names, emails) and request/document metadata.

You define signers using `add_signer_to_request`. Because of the type-safe validation, you know that the required parameters for each signer are present and structured correctly before the request moves forward.

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