How to Use the Growth Strategist MCP in Pydantic AI

Use Pydantic AI to enforce strict type-safe validation on every growth tactic proposed by your agents.

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Connect Growth Strategist MCP to Pydantic AI

Create your Vinkius account to connect Growth Strategist 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 Growth Strategist with Pydantic AI

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Type-safe validation for Pydantic AI

With `validate_growth_tactic`, your agent must return structured data that matches your requirements perfectly. If the strategy lacks a revenue goal or specific audience, the system throws an error immediately. This prevents your agent from passing bad data downstream. By using Pydantic models, you ensure that only high-quality, validated strategy plans reach your final output.

Strict strategy enforcement

Growth Strategist uses your existing Pydantic AI workflow to stop generic advice. It requires the agent to define a unique position and cite evidence in every response. This turns your strategy process into a series of validated steps. If the agent cannot prove its logic, the tool blocks the output, keeping your pipeline clean.

Catch bad strategies early

Use `validate_growth_tactic` to detect blind spots in your agent's thinking before you ever run an experiment. It forces the agent to address the realities of your market. This tool ensures your agent doesn't hallucinate successful outcomes. It demands real data points and measurable business impacts, forcing the agent to be grounded in reality.

Setup guide

Set up Growth Strategist 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": {
        "growth-strategist-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Growth Strategist MCP in Pydantic AI

Every response is validated against a schema. If the tactic doesn't contain the required evidence or outcomes, you get an immediate validation error.

Yes. Because it rejects non-compliant plans, it highlights exactly where your agent's strategy reasoning fails to meet your business standards.

It is built for it. The tool output is structured, allowing your agent to handle validation errors within your existing Python error-handling patterns.

It enforces input constraints at the server level. Only valid strategy structures are accepted, preventing malformed data from corrupting your agent's state.

The data is handled in memory for the duration of the validation call. Your tactical inputs and persona definitions are cleared immediately after the tool processes the request.

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