Edgee

The Edgee MCP server bridges the powerful capabilities of the Edgee platform—organization, project, component, and user management—with AI assistants that communicate via the Model Context Protocol. By exposing a rich set of tools, it allows Claude and other AI assistants to perform administrative operations directly from within an assistant session. Developers can therefore automate routine workflow tasks, such as creating new projects or inviting teammates, without leaving the conversational interface.

At its core, the server translates MCP calls into authenticated requests against the Edgee API. Each tool corresponds to a specific endpoint, enabling CRUD operations on organizations, projects, components, and users. For example, lets an assistant create a new project while the user supplies only a name and description. The server handles authentication through a personal access token, ensuring that all operations respect the permissions of the calling user. This tight integration means developers can embed complex resource‑management logic into prompts or custom actions without writing boilerplate API code.

Key features include comprehensive error handling, which surfaces clear messages for common issues such as missing permissions or invalid IDs. The server is written in TypeScript, providing type safety across the tool definitions and reducing runtime surprises. A full suite of organization tools (, ), project tools (, ), component tools (), and user tools (, ) gives developers granular control over every aspect of their Edgee environment.

Real‑world use cases abound: a data scientist can ask an assistant to spin up a new project for a machine‑learning experiment, while a product manager can invite collaborators via . A DevOps engineer might retrieve component statistics or deploy new component versions using the assistant as a command‑line proxy. Because each tool is stateless and idempotent, they can be safely invoked from automated pipelines or chat‑based workflows.

Integrating Edgee MCP into an AI workflow is straightforward. Once the server is running, any Claude Desktop configuration can register it under , passing the required token via environment variables. From there, prompts can reference tools by name, and the assistant will automatically serialize arguments, invoke the server, and return results in natural language. This seamless connection turns an otherwise manual API interaction into a conversational experience, accelerating development cycles and reducing context switching for teams that rely on Edgee’s robust platform.