Lancerkit is an all-in-one platform for freelancers to manage projects, track time, send invoices, and handle client communication from a single dashboard.

Where do I find my API key?

You can find your API key in the Lancerkit dashboard under Account Settings > Developer API. Generate a new token with appropriate permissions.

Can I create invoices automatically using natural language?

Yes, you can instruct the AI to draft, review, and send invoices to your clients based on your tracked time or fixed project milestones.

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

Name: Lancerkit
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

from crewai import Agent, Task, Crew

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

Connect Lancerkit to any AI agent via MCP.

How to Connect Lancerkit to CrewAI via MCP

Follow these steps to integrate the Lancerkit 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 Lancerkit

Why Use CrewAI with the Lancerkit MCP Server

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

Lancerkit + CrewAI Use Cases

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

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

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

Lancerkit MCP Tools for CrewAI (10)

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

get_client

Retrieve specific metadata of one single client

get_invoice

Retrieve data, payments, and billings for a specific invoice string ID

get_project

Get a single project details by ID

get_status

Examine account and integration connection status overall

get_time_logs

Check the recorded time logs for hours spent

list_clients

List all clients associated with the workspace

list_invoices

Fetch global invoice pipeline statistics

list_projects

List all standard projects

list_services

Fetch all specific billable service items configured online

list_tasks

Check current working tasks

Example Prompts for Lancerkit in CrewAI

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

"Draft an invoice for the Acme Corp redesign project."

"How many billable hours have I tracked this week?"

"Create a new project named Mobile App Development for Delta Tech."

Troubleshooting Lancerkit MCP Server with CrewAI

Common issues when connecting Lancerkit 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.

Lancerkit + CrewAI FAQ

Common questions about integrating Lancerkit 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.