How to Use the Bidsketch MCP in Pydantic AI

Q: Does Pydantic AI support Bidsketch proposal details?

You use getproposaldetails to pull specific document data. The agent treats this as a typed object, allowing you to access fields without manual parsing.

Q: How to connect Bidsketch to Pydantic AI?

Install the slim client and use MCPToolset with your HTTP endpoint. It provides a unified interface for the server. You just define your agent and register the toolset.

Generate type-safe proposals with Pydantic AI. Ensure every Bidsketch action is validated before it hits your account.

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Connect Bidsketch MCP to Pydantic AI

Create your Vinkius account to connect Bidsketch 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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Setup Bidsketch with Pydantic AI

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Type-safe Bidsketch actions for Pydantic AI

Every tool call like `create_proposal` is checked against Pydantic models at runtime. If the API returns garbage, your agent fails immediately. This prevents silent errors in your sales pipeline. You catch issues before they reach your clients.

Client record management for Pydantic AI

Your agent uses `list_clients` to ensure it targets the right person. The server returns structured data that your agent parses into valid objects. It removes the risk of hallucinated fields. Your agent works with data that matches your internal schemas perfectly.

Bidsketch template discovery via Pydantic AI

The agent calls `list_templates` to retrieve your available layouts. It validates the template response before attempting to generate a new document. This keeps your sales process consistent. You know exactly what the agent is doing at every step.

Setup guide

Set up Bidsketch 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": {
        "bidsketch-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Bidsketch MCP in Pydantic AI

The MCP server sends responses that are automatically cast to your Pydantic models. If the server output breaks your schema, the agent raises a validation error. It ensures your data remains clean.

You use `get_proposal_details` to pull specific document data. The agent treats this as a typed object, allowing you to access fields without manual parsing.

Yes, this server works with any model you pass to the agent. Because the validation happens in your code, the underlying model doesn't need to be perfect. Your types enforce the rules.

Install the slim client and use `MCPToolset` with your HTTP endpoint. It provides a unified interface for the server. You just define your agent and register the toolset.

We utilize a zero-trust model where your credentials never leave your local environment. The MCP server handles the handshake via a one-time endpoint token. Your private data is never exposed to our infrastructure.

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