FIWARE MCP Server

The FIWARE MCP Server is the first public implementation of a Model Context Protocol (MCP) server that bridges AI assistants with FIWARE’s ubiquitous Context Broker ecosystem. By exposing a lightweight MCP interface, the server enables Claude and other AI agents to perform CRUD operations on contextual data without needing direct knowledge of FIWARE’s REST APIs. This eliminates the friction that developers face when integrating intelligent agents into edge‑computing or IoT workflows, allowing them to focus on business logic rather than protocol plumbing.

At its core, the server implements three essential tools that mirror common Context Broker operations:

• CB_version – retrieves the broker’s version string, useful for compatibility checks and debugging.
• query_CB – sends arbitrary NGSI queries to the broker and returns JSON results, enabling AI agents to reason over real‑time sensor streams or asset registries.
• publish_to_CB – creates or updates entities in the broker, allowing an assistant to materialize decisions (e.g., a thermostat adjustment) directly into the context store.

These tools are intentionally minimal yet fully functional, making them a solid foundation for more advanced MCP servers that might add authentication, batching, or policy enforcement. The server’s configuration is straightforward: developers can adjust host, port, and timeout values directly in the Python file, ensuring that it fits into existing network topologies or containerised environments.

In practice, the FIWARE MCP Server shines in scenarios where AI-driven automation needs to act on distributed IoT data. For example, a smart building assistant could query occupancy sensors via , infer that a room is empty, and then publish an updated entity to lower HVAC usage. In logistics, a warehouse robot could request inventory status from the broker and publish its position updates for real‑time tracking. Because the MCP interface is language-agnostic, any AI platform that understands MCP—Claude, GPT‑4o, or custom agents—can seamlessly integrate with FIWARE services.

The server’s unique advantage lies in its tight coupling to the Context Broker while remaining agnostic to the underlying FIWARE stack. It abstracts away HTTP headers, NGSI payload formatting, and error handling, presenting developers with a clean toolset that can be invoked directly from an AI prompt. This reduces the cognitive load on developers and accelerates time‑to‑value for IoT‑enabled AI applications.