Ripple-MCP

Ripple addresses a common developer problem: coding agents can understand and modify code, but they often lack direct awareness of what is happening around that code. When a deployment fails, developers still have to manually jump between Git history, CI pipelines, health endpoints, deployment dashboards, documentation, and GitHub pull requests before they can explain the issue to an AI assistant. Ripple solves this by acting as an MCP-based developer operations layer between coding agents and the systems surrounding a project. Through Ripple, an agent such as IBM Bob can access structured tools for recent Git changes, live GitHub Actions status, deployment information, service health, project documentation, and pull-request workflows. This allows the agent to investigate incidents using real operational context instead of relying only on source code. A typical interaction is simple: a developer can ask, “The latest deployment is unhealthy. Investigate what happened and tell me what to fix.” Bob can then use Ripple to check the deployed version, inspect the live service health, review the latest CI run, compare recent code changes, and search project documentation. It can correlate that evidence, identify the root cause, help apply the fix, and then use Ripple to create and track a pull request directly from the IDE. Ripple is designed for software developers, DevOps engineers, platform teams, and teams using AI coding assistants. It is especially useful for developers who want AI assistants to understand both the codebase and the operational environment without constantly switching between tools. What makes Ripple unique is that it does not try to replace the coding agent or build another chatbot. The agent remains responsible for reasoning, while Ripple gives it access to project-specific operational context and actions through MCP. In simple terms: the coding agent understands the code, while Ripple helps it understand what is happening around the code. Ripple is also designed to be lightweight and portable. It can be installed as a CLI, initialized inside any project, and connected to MCP-compatible clients. This makes it easy to integrate into existing developer workflows without requiring a separate hosted platform.