LinearB Connector for AI agents.
7 live capabilities
Track DORA metrics and engineering delivery health in real-time.
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Why people use LinearB
Stop Manual Data Entry with LinearB Engineering Metrics
This Connector changes that by letting your AI agent do the heavy lifting. You can just ask for the cycle time of a specific team or tell your agent to log a new deployment from a Git SHA. You get a live pulse on your engineering health without ever leaving your chat window.
What Vinkius changes
That you get real-time engineering intelligence without the manual dashboard hopping.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Checking team velocity
A manager asks their agent to compare the average cycle time of the Backend team against the Frontend team for the last month.
- Real-world use case 02
Automating release logs
A DevOps engineer tells their agent to report a new deployment for a specific repo using a Git tag, updating the history instantly.
- Real-world use case 03
Audit production stability
A CTO asks for a list of all engineering incidents from the last 48 hours to see if the Change Failure Rate is trending up.
Complete set · 7capabilities
The complete LinearB capability set.
These are the exact actions your AI can choose when you ask it to work with LinearB.
01—04
4 capabilities in this set.
Part of 7 available through LinearB.
- 01 Capability
Record new deployment
Report a new deployment to LinearB by providing a repo ID and Git ref. This keeps your deployment history accurate and updated automatically.
- 02 Capability
Record new incident
Report a new engineering incident with a provider ID and start time. This helps your agent track your MTTR and Change Failure Rate metrics.
- 03 Capability
List software deployments
List recent software deployments from your connected repositories. Use this to quickly see what was shipped and when.
- 04 Capability
List software incidents
List all engineering incidents currently tracked in your account. This helps you audit stability and see recurring issues.
05—07
3 capabilities in this set.
Part of 7 available through LinearB.
- 05 Capability
Query software metrics
Query software engineering metrics like cycle time or coding time for specific ranges. This gives you the raw data needed for performance audits.
- 06 Capability
List engineering teams
List all teams defined in your LinearB workspace. Use this to organize your queries by specific departments or groups.
- 07 Capability
List connected repos
List all the repositories currently connected to your LinearB account. This helps you map out which projects are being tracked by the agent.
Set up in minutes
One URL. Then ask LinearB to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use LinearB from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it LinearB, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable LinearB for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the LinearB URL.
- Step 03
Save and start
Save the connection and enable LinearB in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"linearb": {
"url": "https://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using LinearB
Open Agent mode in chat and ask: "Using LinearB, help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"linearb": {
"url": "https://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using LinearB
Ask Copilot: "Using LinearB, help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"linearb": {
"url": "https://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using LinearB
Open Cascade and ask: "Using LinearB, help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"linearb": {
"url": "https://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using LinearB
Ask Cline: "Using LinearB, help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add linearb --transport http "https://edge.vinkius.com/vk_preview_RQu5BgeMc4kEdSux6KvMTpIFSZDUWY8Nip6OyVZ1/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using LinearB
Ask Claude: "Using LinearB, show me...". 7 tools are ready
Where the request belongs
Work LinearB can move forward.
This is for engineering leaders and DevOps specialists who are tired of manual data entry and want a clear, automated view of their team's delivery health.
Engineering Manager
Uses the Connector to check team cycle times and delivery health via natural language instead of digging through spreadsheets.
DevOps Engineer
Automates the reporting of deployments and incidents directly from their workflow to keep DORA metrics accurate.
CTO
Quickly audits organizational performance and high-level delivery metrics across multiple teams without leaving their workspace.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Monitor and observe your no-code stack via ncScale. track logs, alerts, and tickets directly from your AI agent.
Better Stack
Automate incident management via Better Stack. monitor uptime, manage incidents, and control on-call schedules securely from your AI agent.
Linear (Issue Tracking & PM)
Manage product development via Linear. track issues, monitor sprint cycles, and audit team projects.
Dynatrace (APM and Observability)
Monitor and manage your Dynatrace environment. query metrics, track problems, manage entities, and automate observability workflows directly from your AI agent.
Harness
Automate CI/CD and DevOps workflows via Harness. manage pipelines, executions, and secrets directly from any AI agent.
AppDynamics (Application Performance Monitor API)
Monitor application performance, business transactions, and infrastructure health rules directly from your AI agent.
Bring your own AI
Change the model, client or framework. Keep LinearB connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about LinearB.
The practical details behind the request, access and result.
Does LinearB MCP work with my existing DORA metrics?
Yes, it connects directly to your LinearB account to pull and report DORA metrics like cycle time, deployment frequency, and MTTR.
How do I use LinearB MCP to track deployments?
You can simply tell your AI agent to record a new deployment by providing the repository ID and the Git reference like a tag or SHA.
Can my AI agent report incidents automatically?
Yes, your agent can log new incidents with provider details and start times, which helps keep your delivery health metrics accurate.
What kind of metrics can I get from LinearB MCP?
You can retrieve cycle time, coding time, pickup time, and other aggregated performance data for your engineering teams.
Is LinearB MCP good for seeing team bottlenecks?
It is excellent for this. By querying metrics across different teams, you can quickly identify where work is getting stuck.
How do I connect my repositories to LinearB MCP?
The Connector works with the repositories you have already connected to your LinearB account. It can list all of them for you automatically.
How do I query cycle time for a specific team?
Use the query_software_metrics capability and include the team name or ID in the group_by parameter of your JSON query.
What is the difference between coding_time and pickup_time?
Coding time is the duration from the first commit to the PR creation. Pickup time is the duration from the PR creation to the first review activity.
Can I report a release from the agent?
Absolutely. Use the record_new_deployment capability with the Git SHA or tag and the repository ID to inform LinearB that a deployment has occurred.
One connection away
Give your agent a direct line to LinearB.
Connect LinearB once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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