OpenDigger MCP Server

The OpenDigger MCP Server bridges the gap between raw open‑source repository data and AI assistants, enabling developers to query, compare, and analyze project metrics directly from their IDE. By exposing a rich set of tools and prompts through the Model Context Protocol, it transforms static data into actionable insights that can be woven seamlessly into an AI‑driven workflow. Instead of manually sifting through dashboards or writing custom scripts, a developer can simply ask the assistant to “compare the health of microsoft/vscode and facebook/react” or “analyze contributor growth over two years,” and the server will return structured, ready‑to‑consume results.

At its core, the server offers six powerful tools that cover everything from single metric retrieval () to complex, multi‑repository comparisons (). These tools are built on top of OpenDigger’s analytics engine, which aggregates thousands of GitHub repositories and computes a broad spectrum of metrics—ranging from basic counts like stars and forks to advanced indicators such as bus factor, maintainer count, and community activity. The tool lets users track how these metrics evolve over time, making it ideal for longitudinal studies or release‑cycle monitoring.

Complementing the tools are three thoughtfully crafted prompts that generate narrative reports. produces comprehensive health summaries, offers side‑by‑side competitive analyses, and surfaces patterns in contributor behavior. These prompts enable AI assistants to deliver not just raw numbers but context‑rich explanations, which is especially valuable for product managers or open‑source maintainers who need to justify decisions or communicate status to stakeholders.

Developers benefit from the server’s tight integration with IDEs such as Cursor AI. Once enabled, the MCP appears in the editor’s sidebar, displaying a green status indicator, the count of available tools and prompts, and diagnostic health checks. This visibility ensures that any connectivity or configuration issues are immediately apparent. Moreover, the server’s “server_health” tool (currently in beta) provides real‑time diagnostics, allowing teams to monitor the MCP’s own performance and reliability.

In practice, the OpenDigger MCP Server shines in scenarios where rapid, data‑driven insights are required—whether evaluating the viability of a new open‑source project, benchmarking against competitors, or tracking contributor engagement over time. By embedding these capabilities into an AI assistant’s context, teams can make informed decisions faster, reduce manual overhead, and maintain a continuous feedback loop between code, community metrics, and business strategy.