How do I get my Common Room API token?

Go to **Settings > API Tokens** in Common Room and generate a new token. Copy it and paste it into the field below.

What is a segment in Common Room?

A segment is a group of contacts or organizations defined by specific criteria or manually curated. They help you target and analyze subsets of your community.

Can I track custom activities?

Yes, but you first need to set up an API Signal in Common Room to receive custom activity data. Once configured, the agent can query those activities.

Common Room MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Common Room
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Common Room through Vinkius, pass the Edge URL in the `mcps` parameter and every Common Room 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="Common Room Specialist",
    goal="Help users interact with Common Room effectively",
    backstory=(
        "You are an expert at leveraging Common Room 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 Common Room "
        "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 Common Room MCP Server

Connect your AI assistant to Common Room, the intelligent community growth platform that helps organizations find and build relationships with community members.

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

Contact Search — Find community members by email, name, or external identity across connected platforms.
Segment Management — List all segments, view member counts, and add or remove contacts from specific cohorts.
Activity Tracking — Retrieve activity feeds to understand engagement patterns and identify key contributors.

The Common Room 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 Common Room to CrewAI via MCP

Follow these steps to integrate the Common Room 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 Common Room

Why Use CrewAI with the Common Room MCP Server

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

Common Room + CrewAI Use Cases

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

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

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

Common Room MCP Tools for CrewAI (10)

These 10 tools become available when you connect Common Room to CrewAI via MCP:

add_contact_to_segment

Manually add a contact to a specific segment

get_contact_by_email

Retrieve detailed information about a member by their email

get_contact_tags

Get tags associated with a specific member

get_organization_details

Retrieve details of a specific organization

get_segment_status

Retrieve status and member count for a specific segment

list_activity_types

Retrieve a list of supported activity types in Common Room

list_segment_members

List contacts that belong to a specific segment

list_segments

Retrieve a list of all segments in Common Room

search_contacts

Search for contacts/members in your Common Room

search_organizations

Search for organizations in Common Room

Example Prompts for Common Room in CrewAI

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

"Search for the member with email 'dev@example.com'."

"Show me all segments and their member counts."

"Add 'Alex Chen' to the 'Enterprise Leads' segment."

Troubleshooting Common Room MCP Server with CrewAI

Common issues when connecting Common Room 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.

Common Room + CrewAI FAQ

Common questions about integrating Common Room 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.