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How to Use the WPS 365 MCP in Pydantic AI

Ensure data correctness with WPS 365 using Pydantic AI type validation.

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Pydantic AI

Connect WPS 365 MCP to Pydantic AI

Create your Vinkius account to connect WPS 365 to Pydantic AI 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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Structuring file interactions in WPS 365

The `get_file_info` tool provides a clean, validated structure for document metadata. If an API call returns garbage data, the agent fails hard with Pydantic validation errors—no silent corruption. When you use `list_files`, the resulting list of documents is guaranteed to match the expected schema, making your downstream logic reliable.

Tracking document changes and history

The `get_folder_content` tool gives a validated structure of everything inside a directory. This prevents agents from assuming files exist when they don't. Similarly, the agent can use `list_folders` to map out the entire file hierarchy, knowing each folder object conforms exactly to your defined types.

Managing user and resource access in WPS 365

The MCP Server's tools allow for validated retrieval of users via `list_users`. You can then check who is involved with a document using `list_collaborators`. This system ensures that every piece of organizational data, like what `get_org_info` returns, adheres strictly to the defined type structure.

Setup guide

Set up WPS 365 MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 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": {
        "wps-365-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to WPS 365 tools.",
)

result = await agent.run("List recent WPS 365 transactions")
print(result.output)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by WPS 365. 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 WPS 365 MCP in Pydantic AI

You use the `get_file_info` tool. Because of Pydantic validation, you are guaranteed that the returned metadata fields will be correctly typed and structured.
Yes, use `list_files`. The tool guarantees that the list of files you receive adheres to a strict data model, eliminating unexpected field errors.
The primary data type touched is file metadata. The `get_file_info` tool exposes this, and Pydantic validation ensures that structure is always maintained.
It does. When you call `list_users`, the response payload is strictly validated against your models, meaning you never get unexpected or missing user fields.
The system validates `list_collaborators` and other access controls. This means that when reading collaborator lists, the data structure itself cannot be compromised.

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