How to Use the Modash MCP in Pydantic AI

Type-safe influencer data for your Pydantic AI agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Modash MCP to Pydantic AI

Create your Vinkius account to connect Modash 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 Modash with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe influencer search with Pydantic AI

Every response from `search_instagram` or `search_tiktok` gets validated against your Pydantic models. If the API returns garbage, your agent catches it instantly. This keeps your application logic clean and predictable. You stop worrying about unexpected schema changes breaking your code.

Validated reporting for Pydantic AI agents

Fetch deep analytics using `get_youtube_report`. Your agent validates every integer and string in the report against your type definitions before it processes the data. This ensures your agent only acts on accurate information. You gain confidence in your automated decisions because your data structures are always correct.

Granular influencer data for Pydantic AI

Use `get_raw_profile` to pull specific creator metadata. The Pydantic AI framework enforces your field requirements, so your agent's state remains consistent. It removes the ambiguity of raw API responses. You define the shape of your influencer data, and the server delivers it exactly as you described.

Setup guide

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

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

result = await agent.run("List recent Modash 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 Modash. 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 Modash 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 Modash MCP in Pydantic AI

You define a Pydantic model for each tool response. The framework automatically validates the data returned by the server against your schema.

Definitely. By forcing all MCP responses through your models, you ensure that no malformed data reaches your agent's final decision logic.

The server provides consistent, structured output. You map this output to your models to get the type safety you need for production.

The agent raises a validation error immediately. This stops the process before bad data can corrupt your campaign workflow.

We use encrypted transports and ephemeral sessions. Every influencer record is validated at the boundary, ensuring only authorized data enters your agent's memory.

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