How do I get an API Token for Freshchat?

Log in to Freshchat, navigate to Settings > API Tokens, and click on 'Generate Token' to retrieve your Bearer Token.

What is my 'Region Domain'?

Your domain depends on where your account is hosted (e.g. 'api.freshchat.com' for US, 'api.eu.freshchat.com' for Europe).

Can I send files or images through the agent?

Currently, the 'send_chat_message' tool focuses on sending text content. Supporting rich media typically requires separate upload operations.

Is it possible to see the chat history of a customer?

Yes! Use the 'list_chat_messages' tool and provide the Conversation ID. The agent will retrieve the historical message history for that thread.

Freshchat MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Freshchat
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Freshchat through Vinkius, pass the Edge URL in the `mcps` parameter and every Freshchat 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="Freshchat Specialist",
    goal="Help users interact with Freshchat effectively",
    backstory=(
        "You are an expert at leveraging Freshchat 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 Freshchat "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 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 Freshchat MCP Server

Connect your Freshchat account to any AI agent to automate your customer messaging and conversation management through the Model Context Protocol (MCP). Freshchat is a modern messaging software built for sales and support teams to engage with customers across web, mobile, and social channels. This MCP server enables you to track active chats, send real-time messages, and retrieve detailed user profiles directly through natural conversation.

When paired with CrewAI, Freshchat becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Freshchat tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

Key Features

Conversation Oversight — List all active chats, fetch detailed conversation metadata, and monitor chat statuses (open, resolved) instantly.
Real-time Messaging — Post new messages to existing conversations to keep your support workflows moving fast.
User & Customer Data — Access detailed profile information for chat participants and search for users by email address.
Support Team Insights — List all support agents and team members to maintain full context of who is online and available.
Channel & Group Management — Access configured messaging channels and agent groups to understand your routing logic.
Message History — Retrieve the full message history for any specific conversation ID for audit and reporting.
Multi-Region Support — Seamlessly connect to your specific Freshchat data center (US, EU, IN, AU).

The Freshchat MCP Server exposes 12 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 Freshchat to CrewAI via MCP

Follow these steps to integrate the Freshchat 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 12 tools from Freshchat

Why Use CrewAI with the Freshchat MCP Server

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

Freshchat + CrewAI Use Cases

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

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

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

Freshchat MCP Tools for CrewAI (12)

These 12 tools become available when you connect Freshchat to CrewAI via MCP:

check_account_status

Verify account configuration

get_agent_profile

Get agent metadata

get_chat_user_details

Get user metadata

get_conversation_details

Get chat metadata

list_agent_groups

List agent groups

list_chat_channels

List chat channels

list_chat_messages

List messages in a chat

list_chat_users

List chat participants

list_conversations

List active chats

list_support_agents

List support agents

search_chat_users

Find user by email

send_chat_message

Post a new message

Example Prompts for Freshchat in CrewAI

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

"List all open conversations in my Freshchat account."

"Find the Freshchat user with the email 'customer@example.com'."

"Send a message to conversation 'conv_987': 'I am looking into this for you'."

Troubleshooting Freshchat MCP Server with CrewAI

Common issues when connecting Freshchat 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.

Freshchat + CrewAI FAQ

Common questions about integrating Freshchat 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.