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 CrewAI 10 tools — connect in under 2 minutes

Name: Appbot
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Appbot through Vinkius, pass the Edge URL in the `mcps` parameter and every Appbot tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Appbot Specialist",
    goal="Help users interact with Appbot effectively",
    backstory=(
        "You are an expert at leveraging Appbot tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Appbot "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Appbot becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Appbot tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Appbot MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Appbot

Why Use CrewAI with the Appbot MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Appbot through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Appbot + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Appbot for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Appbot, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Appbot tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Appbot against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Appbot MCP Tools for CrewAI (10)

These 10 tools become available when you connect Appbot to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Appbot + CrewAI FAQ

Common questions about integrating Appbot MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.