Bring Dora Metrics
to OpenAI Agents SDK
Learn how to connect LinearB to OpenAI Agents SDK 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 OpenAI Agents SDK?
The OpenAI Agents SDK auto-discovers all 7 tools from LinearB through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries LinearB, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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Native MCP integration via
MCPServerSse, pass the URL and the SDK auto-discovers all tools with full type safety - —
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
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Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
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First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
LinearB in OpenAI Agents SDK
LinearB and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect LinearB to OpenAI Agents SDK 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 OpenAI Agents SDK
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 OpenAI Agents SDK 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 OpenAI Agents SDK
Every tool call from OpenAI Agents SDK 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 the OpenAI Agents SDK connect to MCP?
Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
Can I use multiple MCP servers in one agent?
Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
Does the SDK support streaming responses?
Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.
MCPServerStreamableHttp not found
Ensure you have the latest version: pip install --upgrade openai-agents
Agent not calling tools
Make sure your prompt explicitly references the task the tools can help with.