AppFollow MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect AppFollow through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="AppFollow Assistant",
instructions=(
"You help users interact with AppFollow. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from AppFollow"
)
print(result.final_output)
asyncio.run(main())
* 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.
The OpenAI Agents SDK auto-discovers all 8 tools from AppFollow through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries AppFollow, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the AppFollow MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 8 tools from AppFollow
Why Use OpenAI Agents SDK with the AppFollow MCP Server
OpenAI Agents SDK provides unique advantages when paired with AppFollow through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
AppFollow + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the AppFollow MCP Server delivers measurable value.
Automated workflows: build agents that query AppFollow, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries AppFollow, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through AppFollow tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query AppFollow to resolve tickets, look up records, and update statuses without human intervention
AppFollow MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect AppFollow to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting AppFollow to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
AppFollow + OpenAI Agents SDK FAQ
Common questions about integrating AppFollow MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect AppFollow with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect AppFollow to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.