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Linear MCP Server for CrewAIGive CrewAI instant access to 11 tools to Check Linear Status, Create Linear Comment, Create Linear Issue, and more

Built by Vinkius GDPR 11 Tools Framework

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

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The Linear app connector for CrewAI is a standout in the Loved By Devs category — giving your AI agent 11 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="Linear Specialist",
    goal="Help users interact with Linear effectively",
    backstory=(
        "You are an expert at leveraging Linear 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 Linear "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
Linear
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Linear MCP Server

Connect your Linear workspace to any AI agent and take full control of your agile software delivery and high-fidelity issue orchestration through natural conversation.

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

  • Issue Portfolio Orchestration — List all active tickets, retrieve detailed high-fidelity metadata, and monitor delivery status programmatically
  • Agile Execution Intelligence — Programmatically generate and update high-fidelity issues for specific teams directly through your agent
  • Project & Cycle Monitoring — Access your complete directory of high-fidelity projects and active cycles to ensure perfectly coordinated development
  • Resource Architecture — List team members and collaborators to understand and orchestrate your organizational structure programmatically
  • Communication Stream Access — Programmatically add high-fidelity comments to specific issues to maintain perfect contextual alignment
  • Operational Monitoring — Verify account-level API connectivity and monitor issue orchestration volume directly through your agent for perfectly coordinated service scaling

The Linear MCP Server exposes 11 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 11 Linear tools available for CrewAI

When CrewAI connects to Linear through Vinkius, your AI agent gets direct access to every tool listed below — spanning issue-tracking, agile, sprint-planning, 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.

check_linear_status

Check API Status

create_linear_comment

Add a comment to an issue

create_linear_issue

Create a new issue

get_linear_issue

Get details for a specific issue

list_linear_cycles

List active cycles

list_linear_issues

List Linear issues

list_linear_labels

List issue labels

list_linear_projects

List active projects

list_linear_teams

List workspace teams

list_linear_users

List workspace members

update_linear_issue

Update an existing issue

Connect Linear to CrewAI via MCP

Follow these steps to wire Linear into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 11 tools from Linear

Why Use CrewAI with the Linear MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Linear through the Model Context Protocol.

01

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

02

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

03

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

04

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Linear + CrewAI Use Cases

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

01

Automated multi-step research: a reconnaissance agent queries Linear for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

02

Scheduled intelligence reports: set up a crew that periodically queries Linear, analyzes trends over time, and generates executive briefings in markdown or PDF format

03

Multi-source enrichment pipelines: chain Linear tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

04

Compliance and audit automation: a compliance agent queries Linear against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Linear in CrewAI

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

01

"List all active issues and show their status."

02

"Create a new issue for the 'Frontend' team titled 'Implement Dashboard'."

03

"Check the team members in the 'Mobile' team."

Troubleshooting Linear MCP Server with CrewAI

Common issues when connecting Linear to CrewAI through the Vinkius, and how to resolve them.

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

Linear + CrewAI FAQ

Common questions about integrating Linear MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.