Swarmia MCP Server

Swarmia MCP Server – Unlocking Enterprise Software Metrics for AI Assistants

The Swarmia MCP Server bridges the gap between advanced AI assistants and the rich analytics layer of Swarmia’s Export API. In modern software organizations, data about code quality, delivery cadence, and investment returns is dispersed across dashboards, spreadsheets, and internal tools. This server consolidates those insights into a single, AI‑friendly interface, enabling assistants like Claude or Cursor to query and interpret enterprise metrics without leaving the conversational context.

By exposing a suite of dedicated tools—pull request metrics, DORA metrics, investment balance reports, software capitalization, and effort reporting—the server provides developers and product managers with immediate, actionable information. For example, a team lead can ask an AI assistant to “show me our pull request cycle time trends for the last quarter,” and the server will return a CSV payload that can be parsed, visualized, or fed into further analysis pipelines. This eliminates the need to manually export data, write custom scripts, or navigate Swarmia’s UI, thereby reducing friction and accelerating decision‑making.

Key capabilities include flexible time framing (predefined windows or explicit start/end dates), timezone awareness, and optional filtering by application or environment for deployment metrics. The investment balance tool pulls effort data tied to financial categories, enabling stakeholders to quantify the human capital invested in each project. The software capitalization endpoints surface employee contributions that qualify for capitalizable work, a critical metric for financial reporting and strategic planning. All outputs are delivered as CSV streams, ensuring compatibility with downstream tools such as BI platforms, spreadsheets, or custom dashboards.

Real‑world use cases span the entire development lifecycle. Product owners can monitor DORA metrics to validate release velocity improvements, while finance teams leverage investment balance reports to justify budget allocations. Compliance officers may audit effort reporting for regulatory purposes, and HR can analyze software capitalization data to assess workforce productivity. By integrating seamlessly with MCP clients, the server fits naturally into existing AI workflows: a single conversational prompt triggers a data fetch, which the assistant can then summarize, visualize, or recommend actions for.

What sets this MCP server apart is its focus on enterprise‑grade metrics and its tight coupling with Swarmia’s Export API. Unlike generic data connectors, it offers domain‑specific tools that understand the nuances of software delivery—cycle times, deployment frequency, and capitalizable effort. This specialization reduces the cognitive load on developers, allowing them to ask natural language questions and receive precise, context‑aware answers that drive faster, data‑driven decisions.