MCP Server – Overview & Use Cases

• Use the MCP server to ask natural-language questions and generate reports from LinearB metrics.
• Explore persona-based use cases for leaders, managers, and executives.
• Start quickly using prebuilt prompts (merge rate, lead time, urgent PRs, release reports).
• Use MCP tools (metrics, repos, PRs, incidents, etc.) to query specific data domains.
• Always verify outputs in the LinearB Dashboard before using results for decisions or publishing.

What to know

• The MCP server is a Beta feature. Behavior and outputs may change before GA.
• Because results are generated through natural language, responses may be incomplete or inaccurate in edge cases.

As a leader, you need more than a performance snapshot. You also need context. Scaling success across squads requires visibility into the practices that drive excellence and inefficiencies that are holding you back.

With the MCP server, you can benchmark performance, identify what enables top contributors, and replicate those strategies across the organization.

Applications

• Benchmark delivery, quality, and throughput metrics across teams to spot strengths and gaps.
• Identify best practices from top contributors and scale them across the org.
• Track consistency to detect workflows or repos that lag consistently, signaling systematic inefficiencies.
• Align internal metrics with industry benchmarks.

Coaching isn’t about instincts; it’s about data-driven insights that make growth conversations meaningful. You need to know where individuals excel and where targeted support matters.

LinearB’s MCP server surfaces contributor-level patterns in productivity, quality, and collaboration. With proper context, you can guide one-on-one conversations and drive continuous improvement.

Applications

• Spot productivity patterns around coding frequency or time allocation, and drill into specifics.
• Surface quality insights by tracking review participation and the balance of new code vs. rework.
• Reveal efficiency gaps by breaking down coding, reviewing, and deployment times.
• Provide actionable feedback using precise data to move coaching from subjective to evidence-based.

Executives and cross-functional partners often want answers, not dashboards. The LinearB MCP server makes engineering data accessible by letting you ask questions in natural language to generate tailored reports instantly.

Applications

• Deliver metrics that matter most, from merge rate to lead time, to empower executives with usable data.
• Run on-demand queries (for example, “Show me cycle time trends for the frontend repo over the last six months”).
• Filter flexibly by teams, contributors, repositories, and timeframes.

These use cases only scratch the surface. With the MCP server, you can turn raw engineering activity into actionable insight. Interactive reports, custom benchmarks, and predictive insights help you scale best practices, coach confidently, and communicate engineering value.

To help you get started, the MCP server includes prebuilt prompts you can use and customize:

• Merge rate report — Track delivery velocity and spot bottlenecks.
• Lead time report — Measure time from work start to completion for predictable delivery.
• Urgent PR report — Identify and resolve critical pull requests that delay deployments.
• Release report — Fetch PRs tied to releases for precise version control and tracking.

The LinearB MCP server exposes tools that let you interact with your organization’s data through Claude or other MCP-compatible clients. Each tool maps to a LinearB data domain, enabling natural-language queries, filtering, and reporting.

The MCP server provides dynamic access to LinearB’s data through natural language. However, as with any generative AI system, it may occasionally return inaccurate or incomplete results.

To ensure accuracy, always verify numbers and metrics in the LinearB Dashboard before making key decisions or publishing derived reports.

Configuring the MCP Server