Bee Agent & Model Context Protocol with Backstage

The Bee Agent & Model Context Protocol (MCP) server bridges the gap between large language models and a Backstage instance, enabling AI assistants to query and manipulate backstage data through a unified protocol. By exposing Backstage’s RESTful API as MCP tools, the server allows developers to give LLMs direct access to internal services such as catalog entities, component metadata, and authentication workflows without exposing raw HTTP endpoints. This abstraction streamlines the integration of AI assistants into existing developer portals, providing a secure and consistent interface for complex operations.

What the Server Solves

Backstage is a powerful platform for managing software catalogs, documentation, and infrastructure. However, its native API requires authentication tokens, careful URL construction, and an understanding of Backstage’s domain model. The MCP server eliminates these hurdles by presenting a declarative set of tools that encapsulate common Backstage interactions. Developers can now ask an LLM to “list all microservices in the production namespace” or “create a new component with a specific tag,” and the MCP server translates those high‑level requests into precise Backstage calls. This reduces boilerplate, prevents credential leakage, and ensures that all API usage follows the same security policies.

Core Features & Capabilities

• Token‑based Authentication: The server configures Backstage to accept static tokens, allowing the MCP client to authenticate via a simple header. This keeps credentials out of the LLM’s prompt while still enabling secure access.
• Tool Exposure: Each Backstage endpoint is wrapped as an MCP tool, exposing a clear name, description, and parameter schema. The LLM can discover these tools through the MCP resource, making integration intuitive.
• Agent Demo: A Bee Agent implementation demonstrates how an AI assistant can invoke the MCP server. The agent loads the tool list, performs a call, and streams results back to the LLM, illustrating a complete workflow from prompt to Backstage interaction.
• Extensibility: The server’s architecture allows developers to add custom tools for other Backstage services or third‑party APIs, making it a versatile middleware layer.

Real‑World Use Cases

• Catalog Management: Automate the creation, update, or deletion of components in Backstage’s catalog by asking an LLM to perform routine tasks.
• Documentation Generation: Use the server to fetch component metadata and generate README files or internal documentation automatically.
• Infrastructure Automation: Trigger CI/CD pipelines or infrastructure changes via Backstage’s plugin APIs, all through natural language commands.
• Onboarding: New developers can interact with Backstage via an AI assistant to discover services, read documentation, or request access without navigating the portal manually.

Integration with AI Workflows

The MCP server fits neatly into existing LLM pipelines. An assistant can first call the resource to enumerate available Backstage operations, then prompt the user for specific parameters. Once a tool is selected, the assistant sends an request with the necessary arguments; the server handles authentication, makes the Backstage call, and returns a structured response. This pattern keeps the LLM focused on natural language understanding while delegating all API interaction logic to the MCP server, ensuring consistency and security across deployments.

Standout Advantages

• Security by Design: By centralizing token handling and API access in the server, sensitive credentials never reach the LLM or end users.
• Developer Productivity: The declarative tool definitions reduce the learning curve for new developers, who can start issuing Backstage commands with minimal setup.
• Reusability: The same MCP server can serve multiple AI assistants or chatbots, making it a single source of truth for Backstage interactions across an organization.

In summary, the Bee Agent & MCP server provides a robust, secure, and developer‑friendly gateway between AI assistants and Backstage, turning complex API interactions into simple conversational commands.