How do I find my AppFollow API Token?

You can find your API token in your AppFollow account settings under the **API** or **Integrations** section.

What is an 'extId' in AppFollow?

The `extId` is the external ID of the app in the store. For iOS apps, it's the numeric Apple ID. For Google Play apps, it's the bundle name (e.g., `com.example.app`).

Does this integration support semantic tags?

Yes, you can use the `get_reviews_semantic` tool to retrieve reviews categorized by their content type, such as 'Bug', 'Feature Request', or 'Pricing'.

AppFollow MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: AppFollow
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

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

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 AppFollow MCP Server

The AppFollow MCP Server brings powerful app store intelligence directly to your AI agent. Monitor your app's reputation, track your position in the charts, and analyze user feedback across all major app stores with ease.

Pydantic AI validates every AppFollow tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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.

Key Features

Review Management — List and search for user reviews across different countries and languages.
AI & Sentiment Analysis — Get AI-generated summaries of user feedback and analyze the overall sentiment of your reviews.
Ranking Tracker — Monitor your app's performance in store charts and track daily changes in visibility.
Rating Metrics — Access current star rating distributions and historical rating trends over time.
App Information — Retrieve detailed metadata and store information for any app on the market.
Competitive Benchmarking — Compare your app's performance against competitors using global store data.

Benefits for Teams

Customer Support — Quickly identify common user issues and bugs reported in reviews.
Product Managers — Use AI summaries to understand user sentiment and prioritize feature requests.
Growth & Marketing — Track rankings and ratings to measure the effectiveness of your ASO and UA efforts.

The AppFollow MCP Server exposes 8 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 AppFollow to Pydantic AI via MCP

Follow these steps to integrate the AppFollow 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 8 tools from AppFollow with type-safe schemas

Why Use Pydantic AI with the AppFollow MCP Server

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

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

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

AppFollow + Pydantic AI Use Cases

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

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

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

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

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

AppFollow MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect AppFollow to Pydantic AI via MCP:

get_account_check

Verify AppFollow account connection

get_app_info

Retrieve basic information about an app from AppFollow

get_rankings

Track app rankings in store charts

get_ratings

Get current star rating distribution

get_ratings_history

Get historical rating data over a period of time

get_reviews_ai_summary

Get an AI-generated summary of recent user reviews

get_reviews_summary

Get a summary of reviews and average rating

list_reviews

List app reviews for a specific app store product

Example Prompts for AppFollow in Pydantic AI

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

"What are the most recent 1-star reviews for my app?"

"Give me an AI summary of user feedback for 'com.example.app'."

"Where does my app rank in the 'Health & Fitness' category in the US today?"

Troubleshooting AppFollow MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

AppFollow + Pydantic AI FAQ

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