How to Use the Linear MCP in CrewAI

Q: Is it possible to filter which Linear tools CrewAI uses?

You can use the toolfilter option to restrict agents to specific tools. This prevents agents from making unauthorized changes to your workspace.

Deploy autonomous agent crews for Linear with CrewAI. Let specialized teams handle your entire issue backlog without manual intervention.

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Connect Linear MCP to CrewAI

Create your Vinkius account to connect Linear 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 with CrewAI

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Claude

Perplexity

Collaborative Linear crews for CrewAI

Assign a researcher agent to `list_linear_issues` while a separate manager agent uses `create_linear_comment` to update stakeholders. They share memory to keep everyone informed. This division of labor prevents context switching. Each agent focuses on a single part of the task, leading to faster issue resolution.

Hierarchical task execution in CrewAI

Structure your agents so a lead agent evaluates `list_linear_projects` before delegating sub-tasks to others. It keeps your operations organized and logical. This setup works best for teams that need to maintain strict sprint velocity. You define the hierarchy and let the crew handle the execution.

Automated backlog health with CrewAI

Run a monitor agent that calls `list_linear_labels` periodically to find stale tasks. It can then flag or archive tickets automatically. This keeps your project board clean of technical debt. It operates in the background while you focus on building features.

Setup guide

Set up Linear 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 tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Linear 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 →

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 Analyst",
        goal="Access and analyze Linear data via MCP.",
        backstory="Expert analyst with direct Linear access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Linear 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 MCP in CrewAI

Yes, by sharing tool access, they can split the work. One agent can fetch the data while another decides on the appropriate update.

You simply pass the server URL in your agent definition. CrewAI handles the connection and tool registration automatically.

You can use the tool_filter option to restrict agents to specific tools. This prevents agents from making unauthorized changes to your workspace.

Agents process issues in parallel or sequential chains. This allows you to manage hundreds of tickets without overwhelming your local system.

The server uses ephemeral sessions. Your issue content, including titles and descriptions, is processed through memory and never persisted in logs or external databases.

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