Vinkius

LinearB MCP. Query metrics and track deployments via your AI client.

LinearB connects your AI agent directly to your software delivery pipeline, automating engineering intelligence and DORA reporting. You can query complex metrics like cycle time or coding duration across multiple teams. It also allows you to report new deployments using Git references and log incidents to accurately calculate MTTR and Change Failure Rate.

LinearB MCP is compatible with Claude Claude
LinearB MCP is compatible with ChatGPT ChatGPT
LinearB MCP is compatible with Cursor Cursor
LinearB MCP is compatible with Gemini Gemini
LinearB MCP is compatible with Windsurf Windsurf
LinearB MCP is compatible with VS Code VS Code
LinearB MCP is compatible with JetBrains JetBrains
LinearB MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Query Team Performance Metrics

Ask about complex metrics like average cycle time, coding duration, or pickup time across specific teams.

Log Software Releases

Inform the system about a new software deployment by providing a Git reference (SHA or tag).

Track Service Outages

Record and list engineering incidents, which is necessary for calculating Mean Time To Recover (MTTR) and Change Failure Rate.

Map Technical Assets

View a comprehensive list of all connected repositories and defined engineering teams in the system.

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AI Agent
LinearB

What AI agents can do with LinearB: 7 Tools for Delivery Intelligence

These tools allow your agent to perform specific actions within LinearB, such as listing teams or recording a new software incident. Use them to gather structured data instantly.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using LinearB MCP

Record New Deployment

Reports a new software release into LinearB using a specific repository ID and Git reference.

Record New Incident

Creates an incident record for service outages, requiring the provider ID and time...

List Software Deployments

Retrieves a list of all recent software deployments recorded in LinearB.

List Software Incidents

Fetches a listing of engineering incidents to track service disruptions.

Query Software Metrics

Queries detailed software engineering metrics, allowing you to specify what data...

List Connected Repos

Retrieves a list of all repositories that have been connected and monitored by LinearB.

List Engineering Teams

Lists every team defined within the LinearB system for scope management.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

LinearB MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The LinearB integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with LinearB, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
LinearB MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LinearB. 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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Policy on each call

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Tracking software health usually means switching between five different tabs.

Right now, tracking delivery performance involves constant context switching. You check the deployment dashboard for recent releases; then you switch to the team management view to see who owns which repo. Next, you open a separate tab just to list out all current incidents and manually calculate the MTTR by looking at timestamps. It's a tedious process of clicking through dashboards and copy-pasting data into summary documents.

With this MCP, that whole routine vanishes. You tell your agent what you need—whether it’s querying cycle time or listing team structures. The agent handles the clicks across all those services behind the scenes. You get one clean answer: a comprehensive view of your engineering performance without touching a dashboard.

LinearB MCP gives you immediate control over incident and deployment tracking.

The biggest manual steps that go away are the need to manually log releases or track incidents. You no longer have to stop your workflow to navigate a UI just to record a new deployment; you simply tell your agent to use `record_new_deployment`. Similarly, logging an outage is as simple as using the `record_new_incident` tool.

It's not about viewing data anymore. It's about controlling the inputs that generate the metrics. You own the historical record of deployments and incidents instantly.

What LinearB MCP does for your AI

Managing software health used to mean opening a dozen dashboards—one for deployments, one for team capacity, another for incident logs. Now, your agent handles the heavy lifting. This MCP lets your AI client access all those critical engineering metrics directly. You can ask natural language questions like, 'What was our average cycle time last month?' and get an immediate answer detailing coding time versus pickup time.

Need to log a new release? Your agent records that deployment using the Git reference, keeping your records current without you lifting a finger. If something breaks, reporting a new incident is just a command away. Because this capability lives in the Vinkius catalog, connecting it takes minutes. You get a single source of truth for performance data—the whole picture needed to audit organizational health and track deployments.

Built · Hosted · Managed by Vinkius LinearB MCP - Track Engineering Metrics & Deployments
Server ID 019d75c7-9e9e-7357-afef-75d61374aa2c
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about LinearB MCP

How do I query cycle time using LinearB MCP? +

You ask your agent directly, specifying the metric and time frame. The query_software_metrics tool handles the complex data request, giving you immediate insight into coding time versus pickup time.

Can I use LinearB MCP to track deployments from CI/CD? +

Yes. You can use your agent to trigger record_new_deployment by passing the Git SHA or tag, ensuring that every release is logged automatically for accurate reporting.

What happens when I list engineering teams with LinearB MCP? +

The list_engineering_teams tool fetches a clean list of all defined teams in the system. This helps you map technical IDs to specific organizational units for better reporting.

Does LinearB MCP help calculate MTTR? +

Yes, by using record_new_incident, your agent logs the start time of an incident against a provider. This critical data point allows you to accurately track and calculate Mean Time To Recover (MTTR).

Which repositories can I query with LinearB MCP? +

First, use list_connected_repos to see all available sources. Then, your agent uses those IDs when calling tools like query_software_metrics or record_new_deployment.