How do I find my Appbot API credentials?

Log in to your Appbot dashboard, go to your team settings, and navigate to the API section. You can generate an API Key which consists of a Username and a Password.

Can I filter reviews for a specific app version?

Yes, you can use the `list_versions` tool to see detected versions and then use the `list_reviews` tool with the version filter to see feedback for that specific release.

What types of sentiment does Appbot detect?

Appbot classifies reviews into four sentiment categories: positive, negative, neutral, and mixed. You can filter reviews using these categories in the `list_reviews` tool.

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

Name: Appbot
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 Appbot 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 Appbot "
            "(10 tools)."
        ),
    )

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

The Appbot MCP Server provides deep insights into your app's user feedback. By connecting your Appbot account to your AI agent, you can programmatically retrieve reviews, analyze sentiment trends, and identify key topics from your iOS, Android, and other platform reviews using natural language.

Pydantic AI validates every Appbot 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

Review Retrieval — List and filter reviews by app, sentiment, star rating, or specific keywords.
Sentiment Analysis — Quickly gauge the overall tone of user feedback (positive, negative, neutral, mixed).
Topic Identification — Discover common themes in your reviews with standard and custom topics.
Version Tracking — Monitor feedback for specific app versions to evaluate new releases.
Global Insights — Filter reviews by country and language to understand your global audience.

The Appbot 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 Appbot to Pydantic AI via MCP

Follow these steps to integrate the Appbot 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 Appbot with type-safe schemas

Why Use Pydantic AI with the Appbot MCP Server

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

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

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

Appbot + Pydantic AI Use Cases

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

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

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

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

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

Appbot MCP Tools for Pydantic AI (10)

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

get_account_info

Retrieve Appbot account details and connection status

get_review_details

Get complete details for a single specific review

get_reviews_by_custom_topic

Retrieve reviews associated with a specific custom topic

list_apps

List all apps tracked by your team in Appbot

list_countries

List countries available for filtering reviews

list_custom_topics

List user-defined custom topics set up in the Appbot dashboard

list_languages

List all languages supported by Appbot for sentiment analysis

list_reviews

Use sentiment, starRating, or keyword filters to narrow down the results. Useful for sentiment analysis and bug reporting. List reviews for a specific app with optional filtering

list_topics

List standard topics identified in app reviews by Appbot AI

list_versions

List app versions detected in the app reviews

Example Prompts for Appbot in Pydantic AI

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

"List all my apps tracked in Appbot."

"Show me the last 10 negative reviews for the iOS app."

"What are the most common topics in recent reviews for my Android app?"

Troubleshooting Appbot MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Appbot + Pydantic AI FAQ

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