Can I add a new lead directly from the chat?

Yes. By invoking the 'create_taskforce_lead' tool and providing the lead's information in JSON format, the AI will register it instantly.

How do I check my pending invoices?

You can use the 'list_taskforce_invoices' tool. The agent will fetch all your invoices and present their statuses.

Is it possible to view the details of a specific customer case?

Yes, using the 'list_taskforce_cases' tool you can query all active support or business cases assigned in your CRM.

INSTANT PLUG AND PLAY

TaskForce MCP Server for CrewAIGive CrewAI instant access to 9 tools to Create Taskforce Case, Create Taskforce Lead, Get Taskforce Customer, and more

Name: TaskForce
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to TaskForce through Vinkius, pass the Edge URL in the `mcps` parameter and every TaskForce 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 TaskForce app connector for CrewAI is a standout in the Sales Automation category — giving your AI agent 9 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="TaskForce Specialist",
    goal="Help users interact with TaskForce effectively",
    backstory=(
        "You are an expert at leveraging TaskForce 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 TaskForce "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 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 TaskForce MCP Server

Connect your AI agent to TaskForce to natively manage your CRM workflow, customer interactions, and invoicing through natural language commands.

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

Lead & Customer Management — Query lists of active leads, fetch detailed customer profiles, and instantly create new lead records on the fly.
Case Tracking — Read and track support or business cases, and generate new cases directly from your chat interface.
Financial Overview — Pull real-time lists of pending invoices and active quotes to monitor business performance without opening a dashboard.

The TaskForce MCP Server exposes 9 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 9 TaskForce tools available for CrewAI

When CrewAI connects to TaskForce through Vinkius, your AI agent gets direct access to every tool listed below — spanning lead-management, case-tracking, invoicing, 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.

create_taskforce_case

Create a new case

create_taskforce_lead

Create a new lead

get_taskforce_customer

Get customer details

get_taskforce_lead

Get lead details

list_taskforce_cases

List all cases

list_taskforce_customers

List all customers

list_taskforce_invoices

List all invoices

list_taskforce_leads

List all leads

list_taskforce_quotes

List all quotes

Connect TaskForce to CrewAI via MCP

Follow these steps to wire TaskForce 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 9 tools from TaskForce

Why Use CrewAI with the TaskForce MCP Server

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

TaskForce + CrewAI Use Cases

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

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

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

Example Prompts for TaskForce in CrewAI

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

"List all active leads in my TaskForce account."

"Create a new lead for John Doe (john@example.com)."

"Fetch the latest invoices and quotes."

Troubleshooting TaskForce MCP Server with CrewAI

Common issues when connecting TaskForce 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.

TaskForce + CrewAI FAQ

Common questions about integrating TaskForce 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.