GrowthBook MCP Server for Pydantic AIGive Pydantic AI instant access to 15 tools to Create Environment, Create Feature, Create Project, and more

Name: GrowthBook
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The GrowthBook MCP Server for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 15 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 GrowthBook "
            "(15 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in GrowthBook?"
    )
    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 GrowthBook MCP Server

Connect your GrowthBook account to any AI agent to streamline your experimentation and feature management workflows through natural language.

Pydantic AI validates every GrowthBook tool response against typed schemas, catching data inconsistencies at build time. Connect 15 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

Feature Management — List, create, and toggle feature flags across production and staging environments to control rollouts.
Project Control — Organize your experimentation roadmap by managing projects, their descriptions, and specific settings.
Environment Visibility — Audit and list all configured environments to ensure flags are deployed correctly across your stack.
Full Lifecycle — Create, update, or delete projects and environments as your infrastructure and team needs evolve.
Deep Inspection — Retrieve detailed metadata for specific features and projects to understand their current configuration and state.

The GrowthBook MCP Server exposes 15 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 15 GrowthBook tools available for Pydantic AI

When Pydantic AI connects to GrowthBook through Vinkius, your AI agent gets direct access to every tool listed below — spanning feature-flags, a-b-testing, experimentation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create environment on GrowthBook

Create a new GrowthBook environment

create

Create feature on GrowthBook

Create a new GrowthBook feature flag (v2)

create

Create project on GrowthBook

Create a new GrowthBook project

delete

Delete environment on GrowthBook

Delete a GrowthBook environment

delete

Delete feature on GrowthBook

Delete a GrowthBook feature flag (v2)

delete

Delete project on GrowthBook

Delete a GrowthBook project

get

Get feature on GrowthBook

Get a single GrowthBook feature flag (v2)

get

Get project on GrowthBook

Get a single GrowthBook project by ID

list

List environments on GrowthBook

g., production, staging) used for per-environment feature flag control. List all GrowthBook environments

list

List features on GrowthBook

List all GrowthBook feature flags (v2)

list

List projects on GrowthBook

List all GrowthBook projects

toggle

Toggle feature on GrowthBook

Toggle a GrowthBook feature flag on or off

update

Update environment on GrowthBook

Update an existing GrowthBook environment

update

Update feature on GrowthBook

Partially update a GrowthBook feature flag (v2)

update

Update project on GrowthBook

Edit an existing GrowthBook project

Connect GrowthBook to Pydantic AI via MCP

Follow these steps to wire GrowthBook into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 15 tools from GrowthBook with type-safe schemas

Why Use Pydantic AI with the GrowthBook MCP Server

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

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

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

GrowthBook + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for GrowthBook in Pydantic AI

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

"List all feature flags for the project 'frontend-v2'."

"Enable the 'dark-mode-beta' feature flag in production."

"Get the details and settings for project ID 'proj_123'."

Troubleshooting GrowthBook MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

GrowthBook + Pydantic AI FAQ

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