Can my agent list all content generated for a specific campaign in GRIN?

Yes. Use the 'list_content' tool with filters for the specific campaign. Your agent will retrieve the posts, stories, and media links associated with that activation flawlessly.

How do I track the ROI of an influencer via chat?

You can use the 'list_conversions' tool. Your agent will retrieve sales and attributed conversion data for specific creators, providing a clear overview of their performance natively.

Can I check the status of product seeding orders through the agent?

Absolutely. Use the 'list_orders' tool. Your agent will fetch the fulfillment statuses for all products sent to creators, ensuring your seeding logistics are on track flawlessly.

GRIN MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: GRIN
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect GRIN through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to GRIN "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in GRIN?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About GRIN MCP Server

Connect your GRIN Creator Management account to any AI agent and take full control of your influencer marketing workflows through natural conversation.

Pydantic AI validates every GRIN tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

CRM Orchestration — List and retrieve detailed creator profiles, social handles, and custom properties natively
Campaign Management — Monitor active influencer campaigns and track specific creator activations flawlessly
Content Oversight — Access and review the library of posts, stories, and media generated by your creators synchronously
Performance Tracking — Retrieve conversion data and ROI metrics attributed to specific influencers flawlessly
Logistics & Seeding — Manage product seeding orders and fulfillment statuses sent to creators natively
Partnership Navigation — List and verify formal brand-creator relationships and manage payouts synchronously

The GRIN MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect GRIN to Pydantic AI via MCP

Follow these steps to integrate the GRIN MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 12 tools from GRIN with type-safe schemas

Why Use Pydantic AI with the GRIN MCP Server

Pydantic AI provides unique advantages when paired with GRIN through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your GRIN integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your GRIN connection logic from agent behavior for testable, maintainable code

GRIN + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the GRIN MCP Server delivers measurable value.

Type-safe data pipelines: query GRIN with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple GRIN tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query GRIN and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock GRIN responses and write comprehensive agent tests

GRIN MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect GRIN to Pydantic AI via MCP:

get_campaign

Get details for a specific campaign

get_contact

Get details for a specific creator

get_me

Get details for the current GRIN account

list_activations

Track creator participations within a campaign

list_campaigns

List active and past influencer campaigns

list_contacts

List all creators/influencers in the CRM

list_content

Access the library of posts and stories generated by creators

list_conversions

Track sales and ROI attributed to influencers

list_orders

Manage product seeding and fulfillment orders

list_partnerships

Manage formal brand-creator relationships

list_payments

List and manage creator payouts

update_contact

Update properties for a specific creator

Example Prompts for GRIN in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with GRIN immediately.

"List my influencer campaigns in GRIN"

"Show the conversion data for @janesmith"

"Check the status of seeding order #GF-88392"

Troubleshooting GRIN MCP Server with Pydantic AI

Common issues when connecting GRIN to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

GRIN + Pydantic AI FAQ

Common questions about integrating GRIN MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your GRIN MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.