How to Use the Linear (Issue Tracking & PM) MCP in CrewAI

Q: Can CrewAI use Linear (Issue Tracking & PM) for autonomous ops?

They can. By combining tools like listissues and listcycles, your crew can autonomously track progress throughout the entire sprint.

Q: How do agents share Linear (Issue Tracking & PM) data?

They use shared memory to pass context. If one agent calls getissue, the other agents can access that data to complete their assigned role.

Deploy autonomous agents to manage Linear (Issue Tracking & PM) tasks using the CrewAI framework.

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Connect Linear (Issue Tracking & PM) MCP to CrewAI

Create your Vinkius account to connect Linear (Issue Tracking & PM) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Linear (Issue Tracking & PM) with CrewAI

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Perplexity

Collaborative Linear (Issue Tracking & PM) monitoring

Assign a monitor agent to watch for new work. It uses `list_issues` periodically and alerts the team if a high-priority task sits idle. Let your moderator agent handle status updates. It uses `get_issue` to gather details before proposing a fix or updating the record.

Hierarchical Linear (Issue Tracking & PM) execution

Structure your crew so one agent manages project scope. It uses `list_projects` to define the board and `list_cycles` to set the pace. Delegate detail work to specialized agents. They call `list_labels` to ensure every task is tagged correctly before moving to the next stage.

Autonomous team and user oversight

Keep your workspace clean by identifying inactive accounts. Your agents call `list_users` to cross-reference active contributors against your team roster. Validate workspace access using `get_viewer`. This ensures your agents are operating within the specific boundaries defined by your workspace permissions.

Setup guide

Set up Linear (Issue Tracking & PM) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Linear (Issue Tracking & PM) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Linear (Issue Tracking & PM) Analyst",
    goal="Access and analyze Linear (Issue Tracking & PM) data via MCP.",
    backstory="Expert analyst with direct Linear (Issue Tracking & PM) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Linear (Issue Tracking & PM) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Linear (Issue Tracking & PM) Analyst",
        goal="Access and analyze Linear (Issue Tracking & PM) data via MCP.",
        backstory="Expert analyst with direct Linear (Issue Tracking & PM) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Linear (Issue Tracking & PM) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Linear. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Linear (Issue Tracking & PM) MCP in CrewAI

Yes. You add the server URL to your agent configuration. The agents then have access to all eight tools to perform their tasks.

They can. By combining tools like `list_issues` and `list_cycles`, your crew can autonomously track progress throughout the entire sprint.

They use shared memory to pass context. If one agent calls `get_issue`, the other agents can access that data to complete their assigned role.

The server runs in an ephemeral sandbox. Your workspace data is only accessed via encrypted connections when an agent requests it.

They access issue content, cycle dates, and team member lists. They cannot read your billing details or private account security keys.

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