Can I reply to a WhatsApp message through the agent?

Yes! Use the `send_chat_message` tool with the conversation ID. As long as your WhatsApp inbox is connected to Chatwoot, the agent will deliver your reply.

How do I see the full history of a chat?

Use the `get_chat_history` tool with the unique conversation ID. Your agent will fetch all previous messages, allowing you to review the entire interaction.

Where do I find my Chatwoot Access Token?

Log in to Chatwoot, click on your profile avatar in the bottom left, and select 'Profile Settings'. Scroll to the bottom to find your personal 'Access Token'.

Chatwoot MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Chatwoot
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Chatwoot through Vinkius, pass the Edge URL in the `mcps` parameter and every Chatwoot 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Chatwoot Specialist",
    goal="Help users interact with Chatwoot effectively",
    backstory=(
        "You are an expert at leveraging Chatwoot 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 Chatwoot "
        "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 Chatwoot MCP Server

Connect your Chatwoot account to any AI agent and take full control of your customer support and engagement through natural conversation. Streamline how you manage chats across Web, WhatsApp, Facebook, and more.

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

Conversation Oversight — List and retrieve details for all active and resolved conversations natively
Live Replying — Send messages to customers in active chat sessions flawlessly
Contact Management — List and retrieve detailed customer contact information and history securely
Inbox Intelligence — Monitor all configured inboxes, including Web widgets and social integrations flawlessly
Agent Tracking — List all support agents and manage team availability in real-time
Message History — Access complete chat histories to understand customer context directly within your workspace

The Chatwoot 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.

How to Connect Chatwoot to CrewAI via MCP

Follow these steps to integrate the Chatwoot 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 8 tools from Chatwoot

Why Use CrewAI with the Chatwoot MCP Server

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

Chatwoot + CrewAI Use Cases

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

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

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

Chatwoot MCP Tools for CrewAI (8)

These 8 tools become available when you connect Chatwoot to CrewAI via MCP:

get_chat_history

Retrieve the message history for a specific conversation

get_contact_details

Get detailed information for a specific customer contact

get_conversation_details

Get detailed information for a specific conversation

list_chatwoot_contacts

List all customer contacts

list_chatwoot_inboxes

List all configured inboxes (Web, WhatsApp, etc)

list_support_agents

List all support agents in the account

list_woot_conversations

List all conversations in the account

send_chat_message

Send a message to a customer in a specific conversation

Example Prompts for Chatwoot in CrewAI

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

"List all active conversations in Chatwoot."

"What did the customer in conversation ID 555 say last?"

"Reply to conversation 555: 'I'll look into this right now for you, Sarah.'"

Troubleshooting Chatwoot MCP Server with CrewAI

Common issues when connecting Chatwoot 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.

Chatwoot + CrewAI FAQ

Common questions about integrating Chatwoot 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.