Can I see the value of my sales pipeline through the agent?

Yes! Use the `list_sales_deals` tool. The agent will return all open deals, and you can ask it to calculate the total value based on the amounts listed in Clientify.

How do I check the last interaction with a specific contact?

Use the `get_contact_crm_details` tool. Your agent will fetch the contact's profile, including recent activities and tags, to give you full context on the relationship.

Where do I find my Clientify API Key?

Log in to your Clientify account, go to **Settings**, select **My Account**, and navigate to the **API** section to generate and copy your token.

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

Name: Clientify
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Clientify through Vinkius, pass the Edge URL in the `mcps` parameter and every Clientify 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="Clientify Specialist",
    goal="Help users interact with Clientify effectively",
    backstory=(
        "You are an expert at leveraging Clientify 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 Clientify "
        "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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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Clientify MCP Server

Connect your Clientify CRM account to any AI agent and take full control of your sales and marketing automation through natural conversation. Streamline how you manage contacts, deals, and daily activities natively.

When paired with CrewAI, Clientify becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Clientify 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 Oversight — List and retrieve details for all contacts including tags and status natively
Deal Intelligence — Access and monitor sales opportunities and deal values flawlessly
Activity Auditing — List and review CRM activities such as calls, emails, and meetings securely
Pipeline Logistics — Monitor sales pipelines to understand your revenue flow flawlessly
Company Management — List all companies stored in your account to maintain B2B relationships securely
User Visibility — Access your own profile and CRM metadata directly within your workspace flawlessly

The Clientify 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 Clientify to CrewAI via MCP

Follow these steps to integrate the Clientify 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 Clientify

Why Use CrewAI with the Clientify MCP Server

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

Clientify + CrewAI Use Cases

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

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

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

Clientify MCP Tools for CrewAI (8)

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

get_contact_crm_details

Get detailed information for a specific contact

get_deal_details

Get detailed information for a specific sales deal

get_my_clientify_profile

Retrieve information about the authenticated CRM user

list_clientify_companies

List all companies stored in Clientify

list_clientify_contacts

List all contacts in Clientify CRM

list_crm_activities

List CRM activities such as calls, emails, and meetings

list_sales_deals

List sales opportunities and deals

list_sales_pipelines

List sales pipelines configured in the account

Example Prompts for Clientify in CrewAI

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

"List my last 5 sales deals in Clientify."

"Show me the details for contact ID '12345'."

"List all active CRM pipelines."

Troubleshooting Clientify MCP Server with CrewAI

Common issues when connecting Clientify 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.

Clientify + CrewAI FAQ

Common questions about integrating Clientify 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.