Bring Dora Metrics
to Mastra AI
Learn how to connect LinearB to Mastra AI and start using 7 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the LinearB MCP Server?
Connect your LinearB account to any AI agent to automate your engineering intelligence and DORA metrics reporting. This MCP server enables your agent to query cycle time, track deployments, and report incidents directly from natural language interfaces.
What you can do
- Metric Ingestion — Query complex engineering metrics including cycle time, coding time, and pickup time across teams
- Deployment Management — Inform LinearB of new software releases by reporting Git refs (SHAs or tags) programmatically
- Incident Tracking — Report and list engineering incidents to maintain accurate Change Failure Rate and MTTR metrics
- Metadata Oversight — List teams and connected repositories to map technical IDs to organizational structures
- DORA Analytics — Retrieve aggregated performance data to identify bottlenecks in your delivery pipeline
How it works
1. Subscribe to this server
2. Enter your LinearB Public API Key
3. Start managing your engineering metrics from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Engineering Managers — Monitor team cycle times and delivery health via simple natural language commands
- DevOps Engineers — Automate the reporting of deployments and incidents directly from CI/CD pipelines or IDEs
- CTOs — Quickly audit organizational performance and DORA metrics without opening the dashboard
Built-in capabilities (7)
List all connected repositories
List all teams defined in LinearB
List recent deployments
List engineering incidents
Requires a JSON body with requested_metrics and time_ranges. Query software engineering metrics (v2)
Requires repo_id and ref. Report a new deployment to LinearB
Requires provider_id and started_at. Report a new incident
Why Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and LinearB tool infrastructure. Connect 7 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
- —
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add LinearB without touching business code
- —
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
- —
TypeScript-native: full type inference for every LinearB tool response with IDE autocomplete and compile-time checks
- —
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
LinearB in Mastra AI
LinearB and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect LinearB to Mastra AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LinearB in Mastra AI
The LinearB 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. All 7 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Mastra AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
LinearB for Mastra AI
Every tool call from Mastra AI to the LinearB MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I query cycle time for a specific team?
Use the query_software_metrics tool 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 tool with the Git SHA or tag and the repository ID to inform LinearB that a deployment has occurred.
How does Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp