Where do I find my Secret Key?

Log in to Polaria, go to Settings > Marketplace > Create my own app, create a new application, and show the 'Secret Key' in the authorized applications section.

What is the Base URL for the API?

The Polaria REST API v2 base URL is: https://polaria.ai/rest/v2/

Can I modify existing conversations?

Yes, you can add replies and change the status of existing conversations directly using the Polaria MCP.

INSTANT PLUG AND PLAY

Polaria MCP Server for CrewAIGive CrewAI instant access to 8 tools to Add Chat Message, Create Contact, Get Contact, and more

Name: Polaria
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 8 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Polaria app connector for CrewAI is a standout in the Communication Messaging category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Polaria Specialist",
    goal="Help users interact with Polaria effectively",
    backstory=(
        "You are an expert at leveraging Polaria 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 Polaria "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 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 Polaria MCP Server

Transform your customer support operations by connecting Polaria directly to your AI agent. Let your assistant automatically retrieve relevant help articles, instantly respond to customer conversations, and efficiently manage your user directory without navigating away from your central workspace.

When paired with CrewAI, Polaria becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Polaria 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

Access and organize your entire customer contact database
Read and respond to live chat conversations instantly
Update the status of support tickets (Open, Pending, Resolved)
Retrieve FAQ articles to resolve customer inquiries faster
Manage custom attributes for targeted support

Who is it for?

Ideal for customer success teams, support agents, and community managers who want to resolve user queries faster and automate repetitive chat tasks.

The Polaria MCP Server exposes 8 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.

All 8 Polaria tools available for CrewAI

When CrewAI connects to Polaria through Vinkius, your AI agent gets direct access to every tool listed below — spanning contact-management, conversational-ai, faq-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_chat_message

Add a message to a conversation

create_contact

Create a new contact in Polaria

get_contact

Get details of a specific contact

get_conversation

Get details of a specific conversation

list_contacts

List contacts in Polaria

list_conversations

List conversations in Polaria

list_faqs

List FAQs in Polaria

list_widgets

List Polaria widgets

Connect Polaria to CrewAI via MCP

Follow these steps to wire Polaria into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 8 tools from Polaria

Why Use CrewAI with the Polaria MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Polaria 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

Polaria + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Polaria 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 Polaria, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Polaria 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 Polaria against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Polaria in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Polaria immediately.

"List all contacts in Polaria."

"Show recent chat conversations."

"Add a reply message to conversation 'C123'."

Troubleshooting Polaria MCP Server with CrewAI

Common issues when connecting Polaria 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.

Polaria + CrewAI FAQ

Common questions about integrating Polaria 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.