Mindpilot MCP

Mindpilot MCP is a lightweight, self‑contained server that bridges AI assistants with a powerful visualisation engine. Its core purpose is to let developers see the code they are working on through automatically generated architecture, flow and process diagrams. By keeping all rendering locally, it eliminates the need to send source files to external services, thereby preserving privacy and reducing latency. For teams that rely on Claude, Cursor, VS Code, Windsurf or Zed, Mindpilot provides a single configuration point that unlocks on‑demand visual insights directly inside the tool of choice.

The server exposes a set of MCP resources that let an LLM ask for diagrams, request diagram history, or export vector images. When a user requests a diagram, the LLM sends a prompt that describes the desired view (e.g., “show me the dependency graph of this module”). Mindpilot parses the prompt, introspects the local codebase, and returns a structured diagram in SVG format. The diagram is then rendered within the assistant’s UI or a dedicated web interface that all connected clients share. Because the server runs locally and can be started once for multiple assistants, developers can work across several windows or IDEs without port conflicts; the shared web server aggregates all diagram history in a single place.

Key capabilities include:

• Instant architecture generation – turn code into layered, component‑level diagrams on demand.
• Process flow visualization – map out complex control flows, state machines or data pipelines without manual effort.
• Redundancy detection – AI‑generated “vibe checks” highlight unused or duplicated code paths, helping teams clean up legacy bases.
• Secure local processing – all rendering happens on the developer’s machine; no code leaves the local environment.
• Export options – diagrams can be exported as vector images for documentation, presentations or version control.

Typical use cases span from onboarding new team members—who can quickly grasp system structure—to refactoring large codebases, where visual feedback guides which modules to decouple. Architects can also use Mindpilot to validate design decisions before implementation, while QA engineers may generate test‑coverage diagrams to spot gaps. In continuous integration pipelines, a lightweight script could spawn Mindpilot to produce up‑to‑date diagrams that are then attached to build artifacts.

By integrating seamlessly with popular AI workflows, Mindpilot MCP offers a unique blend of privacy‑preserving visual analytics and effortless multi‑client support. Its ability to share a single diagram history across multiple assistants, combined with zero‑dependency local rendering, makes it an indispensable tool for developers who want to “see through their agent’s eyes” and keep complex systems understandable.