How to Use the Better Proposals MCP in Pydantic AI

Q: How do I configure the Better Proposals MCP Server with Pydantic AI?

Install the MCP-enabled framework and instantiate MCPToolset pointing to your Vinkius endpoint. Pass this toolset directly to your agent's constructor to begin validation.

Build type-safe document pipelines with Pydantic AI to validate proposals and client contacts at runtime.

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Connect Better Proposals MCP to Pydantic AI

Create your Vinkius account to connect Better Proposals 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 Better Proposals with Pydantic AI

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Validate proposal data structures at runtime

`create_proposal` generates new agreements using strict input parameters that Pydantic AI validates before execution. If your model tries to pass an invalid date or missing field, the framework catches it. This eliminates silent errors in your document pipeline. You get immediate feedback if a template pulled via `list_templates` doesn't match the expected schema.

Type-safe contact management for your MCP Server

`create_contact` adds new clients to your account while enforcing strict type constraints on emails, phone numbers, and company names. The agent reads existing records using `get_contact` and `list_contacts`. Using this MCP Server ensures that dirty data never corrupts your CRM. Errors trigger immediate failures, keeping your customer database clean.

Track document status without schema drift

`get_proposal` fetches live status and pricing data for any active agreement in your pipeline. Your agent can also call `list_proposals` to audit your entire sales pipeline. Every response is parsed directly into Pydantic models. This means your application code can safely reference proposal values without worrying about unexpected null fields or broken types.

Setup guide

Set up Better Proposals 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": {
        "better-proposals-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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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 Better Proposals. 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 Better Proposals MCP in Pydantic AI

Install the MCP-enabled framework and instantiate `MCPToolset` pointing to your Vinkius endpoint. Pass this toolset directly to your agent's constructor to begin validation.

Yes, the framework is completely model-agnostic. You can run these document tools with Anthropic, Gemini, or local models while maintaining strict type validation.

The framework raises a validation error immediately. This prevents your agent from making decisions based on corrupted or hallucinated API responses.

No, Vinkius hosts and manages the server externally. Your agent connects to the hosted endpoint using the secure SSE or HTTP transport layer.

Authentication is handled via a single secure token, bypassing the need to share raw API keys with your agent. All data processed by `get_analytics` remains encrypted in transit and sandboxed.

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