How to Use the Clearstory MCP in Pydantic AI

Strict type-safe construction data management for your Pydantic AI workflows.

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Connect Clearstory MCP to Pydantic AI

Create your Vinkius account to connect Clearstory 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 Clearstory with Pydantic AI

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Pydantic AI agents with validated COR data

Your agent calls `list_change_order_requests` and Pydantic AI checks the response against your schema immediately. If the API returns junk, the agent crashes before processing bad data. This ensures your financial records stay accurate. The agent uses `get_cor_details` to fill out your models, guaranteeing every field matches your type definitions.

Field tag processing in Pydantic AI

Capture field T&M tags using `list_tm_tags` and pass them into your type-safe agent. Pydantic AI rejects any data that doesn't fit your strict input requirements. This stops silent corruption. Your agent processes the validated data to generate reports, ensuring every labor and material cost is accounted for correctly.

Contract validation for Pydantic AI

Query `list_project_contracts` to pull valid contract data into your system. Pydantic AI handles the response, ensuring no hallucinated fields leak into your logs. Your agent maintains state by keeping these contracts linked to change orders. Because you use strict types, your agent provides a reliable audit trail for every project transaction.

Setup guide

Set up Clearstory 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": {
        "clearstory-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Clearstory MCP in Pydantic AI

Install the slim MCP package and initialize an MCPToolset with your server URL. Pass this toolset into your Agent constructor to enable type-safe tool execution.

Yes. Every tool response is validated against your Pydantic models at runtime. If the API doesn't match your schema, the agent throws a validation error immediately.

Pydantic AI catches it during the validation step. You avoid silent corruption because the agent refuses to proceed with malformed data.

The server uses Streamable HTTP and SSE. Just point the toolset at your endpoint and the framework handles the connection for you.

All data flows through an encrypted, ephemeral session. Your T&M tags and contracts are processed in memory and cleared once the request finishes, keeping your records private.

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