How to Use the Carta MCP in Pydantic AI

Q: How does Pydantic AI ensure my Carta data is correct?

When this server returns data from a tool like getcaptable, Pydantic AI parses it into a model you define. If any field is missing, has the wrong type, or fails a custom validation rule, it throws an error instead of letting your agent use bad data.

Q: What happens if the Carta API changes unexpectedly when using Pydantic AI?

Your agent will fail loudly with a ValidationError. This is the core benefit of using Pydantic AI with Carta—you find out immediately that the data from a tool like listshareclasses has changed, preventing your agent from making bad decisions.

Get type-safe, validated Carta data in your Python agent with Pydantic AI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Carta MCP to Pydantic AI

Create your Vinkius account to connect Carta 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.

GDPR Free for Subscribers

Setup Carta with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Get Correct Cap Table Data, Guaranteed

This server lets your agent call `get_cap_table` or `list_stakeholders` to get raw data from Carta. But when you use Pydantic AI, you're not just hoping the data is correct. Every single response is automatically validated against your Pydantic models at runtime. If the API returns an unexpected null or a string instead of an integer, your agent will raise a `ValidationError` on the spot. This stops data corruption before it starts.

Build Model-Agnostic Financial Agents

Pydantic AI doesn't lock you into a single LLM provider. You can build an agent that uses this Carta MCP server with models from OpenAI, Anthropic, Google, or even one running locally. The tools, like `list_funding_rounds` and `list_securities`, work the same regardless. This gives you the freedom to choose the right model for the job. Use a powerful model for complex analysis of convertible notes from `list_convertibles`, and a faster, cheaper model for simple lookups with `get_company`. Pydantic AI handles the abstraction.

A Simple, Reliable MCP Server Connection

Connecting Pydantic AI to this server is clean. You create an `MCPToolset` with the server URL and pass it to your agent. There's no manual tool definition or complex configuration needed; it just works. The framework handles all the HTTP communication, letting your agent focus on its actual task. It can ask for the latest 409A valuation with `list_valuations`, and you can be certain that the response object your code gets matches the Pydantic model you defined.

Setup guide

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

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Carta. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Carta now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Carta MCP in Pydantic AI

When this server returns data from a tool like `get_cap_table`, Pydantic AI parses it into a model you define. If any field is missing, has the wrong type, or fails a custom validation rule, it throws an error instead of letting your agent use bad data.

Yes. Pydantic AI is model-agnostic, so you can configure it to use any compatible local or remote LLM. The agent will still use this Vinkius-hosted server to securely interact with the Carta API.

Your agent will fail loudly with a `ValidationError`. This is the core benefit of using Pydantic AI with Carta—you find out immediately that the data from a tool like `list_share_classes` has changed, preventing your agent from making bad decisions.

You get a managed tool server combined with the safety of runtime type-checking. You don't have to build or host the Carta integration, and you get a strong guarantee that the data your agent works with is exactly what your Python code expects.

Vinkius processes your Carta data, like cap tables and security lists, in a secure, single-use sandbox for each request. Pydantic AI runs in your own environment, so the validated data objects only exist within your application's process. The request is stateless and tied only to your auth token.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript