How do I find my Linear Personal API Key?

Go to [**Linear Settings > API**](https://linear.app/settings/api) and click **Create API Key**. Give it a descriptive name like 'Vinkius MCP' and copy the generated key immediately — it won't be shown again.

Can I create new issues with assignees and labels?

Yes! Use the `create_issue` tool with the required `team_id` and `title` parameters. Optionally provide `assignee_id`, `priority` (0-4), `description` in Markdown and `label_ids` as a comma-separated list. The agent will return the created issue's identifier and URL.

Does the agent have access to delete issues or modify team settings?

No. This server focuses on read operations and safe mutations — creating issues, updating fields and adding comments. Destructive actions like deletion or team configuration changes are not exposed, keeping your workspace secure.

Linear MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Linear
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Linear through the 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.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

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 12 available tools "
        "and what they can do."
    ),
)

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

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 issue tracking and sprint workflows 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 the Vinkius with zero configuration overhead.

What you can do

User & Team Discovery — Retrieve the authenticated user profile and list all teams configured in your Linear workspace
Issue Management — List, search, inspect and create issues with full metadata including assignees, labels, priority and state
Project Oversight — Browse all active projects, view their status and drill into specific project details by ID
Comments & Collaboration — Add comments to issues to keep your team context aligned without switching to the Linear app
Cycle Tracking — List all sprint cycles for any team, including start/end dates and completion progress
Label Organization — View all issue labels used for categorization across teams

The Linear MCP Server exposes 12 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 Linear to CrewAI via MCP

Follow these steps to integrate the Linear 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 12 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.

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 the 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

Linear + CrewAI Use Cases

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

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

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

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

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

Linear MCP Tools for CrewAI (12)

These 12 tools become available when you connect Linear to CrewAI via MCP:

create_comment

The body supports Linear Markdown format including @mentions and ~~strikethrough~~. Add a comment to a Linear issue

create_issue

Requires the team ID and issue title. Optionally set description, assignee, priority (0=No priority, 1=Urgent, 2=High, 3=Normal, 4=Low) and label IDs. Create a new Linear issue

get_issue

Use the issue ID (UUID) or the human-readable identifier (e.g. TEAM-123). Get full details for a Linear issue

get_project

Get details for a specific Linear project

get_viewer

Useful to verify which account the API token belongs to. Get current authenticated Linear user details

list_cycles

Each cycle has a number, name, start date, end date and completion progress percentage. List Linear cycles (sprints) for a team

list_issues

Optionally filter by team ID to get issues for a specific team only. List Linear issues

list_labels

Optionally filter by team ID. Each label has a name, color and optional description. List Linear issue labels

list_projects

Projects group issues across multiple teams. Use optional limit to control how many results to fetch. List Linear projects

list_teams

Each team has a unique ID, name, key prefix and optional description. Use this to discover teams before querying their issues or cycles. List all Linear teams

search_issues

Optionally filter results to a specific team. Returns issues with identifier, title, state, priority, assignee and URL. Search Linear issues by text

update_issue

Provide the issue ID (UUID) and only the fields you want to change. Update an existing Linear issue

Example Prompts for Linear in CrewAI

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

"Show me all unresolved issues assigned to the Engineering team."

"Create a new issue in the Backend team titled 'Add rate limiting to /api/search endpoint' with high priority."

"What's the current sprint cycle progress for the Mobile team?"

Troubleshooting Linear MCP Server with CrewAI

Common issues when connecting Linear 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

The 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.

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.