Can my AI agent find a specific task by its human-readable code like WEB-42?

Yes! Use the `get_task_by_code` tool with the task code (e.g., WEB-42). Your agent will return the full task details including description, assignees, workflow status, labels, sprint association, time estimates, and checklist progress — in seconds.

I want to quickly see what I need to work on today. Can the agent help?

Absolutely. Use `my_today_tasks` to see everything due today, or `my_tasks` for your full assignment list across all workspaces. The agent returns task titles, project context, due dates, and current workflow status — your daily standup briefing in one command.

Can the agent manage task assignments and checklists too?

Yes. Use `assign_member` and `unassign_member` to manage task assignments by username. For checklists, use `create_checklist_item` to add items (including nested sub-items via parent_id), and `toggle_checklist_item` to mark them done. The complete task lifecycle is covered — from creation to completion.

GitScrum Tasks MCP Server for CrewAI 28 tools — connect in under 2 minutes

Name: GitScrum Tasks
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 28 Tools Framework

Connect your CrewAI agents to GitScrum Tasks through Vinkius, pass the Edge URL in the `mcps` parameter and every GitScrum Tasks tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="GitScrum Tasks Specialist",
    goal="Help users interact with GitScrum Tasks effectively",
    backstory=(
        "You are an expert at leveraging GitScrum Tasks 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 GitScrum Tasks "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 28 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 GitScrum Tasks MCP Server

What you can do

Full task lifecycle — create, update, delete, and toggle completion on tasks with rich metadata including types, effort levels, and dates
Advanced filtering — query tasks by status, sprint, user story, assignee, label, type, effort, workflow column, blocker flag, and date ranges
Subtask management — list, link, unlink subtasks and discover related tasks across your project
Checklists — add checklist items with sub-items and toggle completion for granular progress tracking
Team coordination — assign and unassign members, duplicate tasks, move between projects, and set story points
Comments — list, create, update, and delete task comments for rich collaboration context

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

The GitScrum Tasks MCP Server exposes 28 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 GitScrum Tasks to CrewAI via MCP

Follow these steps to integrate the GitScrum Tasks 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 28 tools from GitScrum Tasks

Why Use CrewAI with the GitScrum Tasks MCP Server

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

GitScrum Tasks + CrewAI Use Cases

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

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

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

GitScrum Tasks MCP Tools for CrewAI (28)

These 28 tools become available when you connect GitScrum Tasks to CrewAI via MCP:

assign_member

Assign a user to a task

create_checklist_item

Use parent_id to create sub-items. Add a checklist item to a task

create_comment

Supports rich text content. Add a comment to a task

create_task

Create a new task

create_task_type

g., Chore, Tech Debt) with a hex color code. Create a new task type

delete_comment

Delete a comment

delete_task

This action cannot be undone. Delete a task permanently

duplicate_task

Duplicate a task

get_task

Get task details by UUID

get_task_by_code

g., WEB-42) instead of UUID. Get task by human-readable code

link_subtask

Link an existing task as a subtask

list_checklists

List checklists on a task

list_comments

Comments support rich text. List comments on a task

list_effort_levels

List effort/priority levels

list_subtasks

List subtasks of a task

list_task_types

) with their colors. List task types in a project

list_tasks

Filter by status (todo, in-progress, done), sprint, user_story, users, labels, type, effort, workflow, is_blocker, is_archived, unassigned, created_at (YYYY-MM-DD=YYYY-MM-DD), closed_at, per_page. List tasks with advanced filters

move_task_to_project

Move a task to a different project

my_tasks

Get all tasks assigned to me

my_today_tasks

Get tasks due today

related_tasks

Get tasks related to a task

set_task_estimate

Set story points / estimate for a task

toggle_checklist_item

Toggle a checklist item done/undone

toggle_task_done

Toggle task completion status

unassign_member

Remove a user from a task

unlink_subtask

Unlink a subtask

update_comment

Edit an existing comment

update_task

Update an existing task

Example Prompts for GitScrum Tasks in CrewAI

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

"Show me all in-progress tasks in the web-app project."

"Create a bug task 'Login timeout on slow connections' in web-app and assign it to janedoe."

"Add a checklist to task WEB-42 with items for 'Write unit tests', 'Update docs', and 'Deploy to staging'."

Troubleshooting GitScrum Tasks MCP Server with CrewAI

Common issues when connecting GitScrum Tasks 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.

GitScrum Tasks + CrewAI FAQ

Common questions about integrating GitScrum Tasks 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.