How to Use the Appfigures MCP in CrewAI

Q: Can a CrewAI agent access multiple Appfigures developer accounts?

Yes. Your research agent can run getexternalaccounts to discover all linked storefronts, allowing the entire crew to split up and analyze different stores simultaneously.

Deploy a specialized team of CrewAI agents to analyze Appfigures store data and optimize your keyword strategy.

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Connect Appfigures MCP to CrewAI

Create your Vinkius account to connect Appfigures to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Appfigures with CrewAI

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Collaborative Store Optimization with CrewAI

Assign one agent to watch rankings while another analyzes revenue. By exposing `get_ranks` and `get_revenue_report` to your crew, they share context to find correlations between visibility and sales. The researcher agent pulls data, the analyst agent calculates the return on investment, and the writer drafts your weekly report. They collaborate autonomously without you writing glue code.

Automated Competitor Analysis

Let your crew scout the market. An agent can run `search_products` to find competing apps, then use `get_ranks` to see where they outshine your own products. This setup lets your agents map out competitor strategies. They identify gaps in your metadata and suggest immediate keyword updates based on hard data.

Automated Customer Sentiment Loops

Keep your product team aligned with user feedback. One agent pulls reviews using `list_reviews`, while a moderator agent categorizes bugs and feature requests. The crew correlates negative reviews with recent updates found via `get_sales_report`. This lets you pinpoint exactly which app version introduced a bug.

Setup guide

Set up Appfigures MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Appfigures tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Appfigures Analyst",
    goal="Access and analyze Appfigures data via MCP.",
    backstory="Expert analyst with direct Appfigures access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Appfigures transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Appfigures Analyst",
        goal="Access and analyze Appfigures data via MCP.",
        backstory="Expert analyst with direct Appfigures access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Appfigures transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Appfigures. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Appfigures MCP in CrewAI

Pass your Vinkius MCP Server HTTP URL directly into the agent's mcps list. For advanced setups, use MCPServerHTTP to filter which Appfigures tools each specific agent can access.

Yes. Your research agent can run `get_external_accounts` to discover all linked storefronts, allowing the entire crew to split up and analyze different stores simultaneously.

CrewAI agents use shared memory. When the analyst agent calls `get_subscriptions_report`, the resulting active and churn metrics are instantly accessible to the strategy agent planning your next campaign.

Yes, you can use a tool filter. This prevents your copywriter agent from accessing `get_revenue_report` while allowing your financial analyst agent full access to earnings data.

Your credentials and app store review texts are transmitted securely over HTTPS directly to your running crew. Vinkius handles the MCP connection in an ephemeral, zero-trust environment, ensuring no marketing or financial data is ever stored permanently on our platform.

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