How do I find my PartnerStack API Key?

In your PartnerStack dashboard, go to **Settings** > **Integrations** and look for the API Key section. You may need to generate a new key if one doesn't exist.

Can I see leads submitted by a specific partner?

Yes! Use the `list_partner_leads` tool. You can ask the AI agent to filter the results for a particular partner name or ID from the retrieved list.

Does this support reward tracking?

Absolutely. Use the `list_partner_rewards` tool to see a log of all generated rewards and their current status across your partner ecosystem.

PartnerStack MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: PartnerStack
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect PartnerStack 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 PartnerStack "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 PartnerStack MCP Server

Connect your PartnerStack account to any AI agent and take full control of your partnership and ecosystem workflows through natural conversation.

Pydantic AI validates every PartnerStack tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

Partner Oversight — List all partners and retrieve detailed metadata to manage your ecosystem relationships.
Lead Tracking — List and retrieve details for leads submitted by your partners to monitor the sales pipeline.
Customer Management — List customers associated with specific partners to understand attribution.
Reward Monitoring — List generated rewards and payouts to ensure your partners are incentivized correctly.
Campaign & Group Analysis — List partner groups and campaigns to maintain a clear view of your program structure.

The PartnerStack MCP Server exposes 10 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 PartnerStack to Pydantic AI via MCP

Follow these steps to integrate the PartnerStack 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 10 tools from PartnerStack with type-safe schemas

Why Use Pydantic AI with the PartnerStack MCP Server

Pydantic AI provides unique advantages when paired with PartnerStack 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 PartnerStack integration code

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

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

PartnerStack + Pydantic AI Use Cases

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

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

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

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

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

PartnerStack MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect PartnerStack to Pydantic AI via MCP:

get_partner

Get details for a specific partner

get_partner_customer

Get details for a specific customer

list_partner_campaigns

List all partner campaigns

list_partner_customers

List all customers associated with partners

list_partner_groups

List all partner groups

list_partner_leads

List all leads submitted by partners

list_partner_rewards

List all generated rewards

list_partner_transactions

List all partner transactions

list_partner_webhooks

List all configured webhooks

list_partners

List all partners

Example Prompts for PartnerStack in Pydantic AI

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

"List all active partners in my account."

"Show me the last 5 leads submitted by our partners."

"What is the status of the rewards for the 'Summer Campaign'?"

Troubleshooting PartnerStack MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

PartnerStack + Pydantic AI FAQ

Common questions about integrating PartnerStack 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 PartnerStack MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.