How to Use the Fera.ai MCP in CrewAI

Q: How do I assign Fera.ai tools to specific CrewAI agents?

Use the toolfilter in your agent definition. This ensures that only the relevant agent has access to specific tools like listreviews.

Deploy specialized CrewAI agents to monitor, moderate, and manage your Fera.ai social proof ecosystem with autonomous team collaboration.

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Connect Fera.ai MCP to CrewAI

Create your Vinkius account to connect Fera.ai 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 Fera.ai with CrewAI

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Autonomous CrewAI Monitoring Teams

Set up a research agent to call `list_reviews` while a moderator agent uses `get_review` to filter content. Your crew works together to manage your store's reputation without you touching a button. It allows for hierarchical operation. One agent gathers the data, and the other makes the final decision on what to display.

Shared Memory for Fera.ai Tool Outputs

CrewAI agents share context from `get_product_rating`, letting your team of agents build a complete picture of your store health. Each agent knows what the other has already checked. This prevents redundant API calls. Your agents stay efficient by building a shared knowledge base of your current product ratings.

Content Moderation with CrewAI

Use `list_media` to let your agents scan customer photos and videos for brand compliance. The agents can flag inappropriate UGC for your review before it reaches your site. It automates the tedious parts of content management. Your agents handle the heavy lifting, leaving you to focus on high-level strategy.

Setup guide

Set up Fera.ai 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 Fera.ai tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Fera.ai 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="Fera.ai Analyst",
        goal="Access and analyze Fera.ai data via MCP.",
        backstory="Expert analyst with direct Fera.ai access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Fera.ai 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 Fera.ai. 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 Fera.ai MCP in CrewAI

Use the tool_filter in your agent definition. This ensures that only the relevant agent has access to specific tools like `list_reviews`.

Absolutely. By sharing memory, your agents can pass findings from one to another, allowing for complex multi-step analysis of store feedback.

Yes. You can add more agents to your crew to handle higher volumes of reviews or to monitor more stores simultaneously.

The framework reports errors directly to the agent. You can configure a secondary agent to act as a supervisor that catches and logs failed tool calls.

Customer feedback and interaction logs are scoped to the specific agent session. The data is never stored permanently by the server, ensuring privacy during the autonomous process.

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