Climatiq MCP Server

The Climatiq MCP Server bridges AI assistants with the Climatiq carbon‑emission API, allowing real‑time calculations of greenhouse gas outputs for a wide range of activities. By exposing a set of tools that encapsulate Climatiq’s endpoints, the server gives developers an easy way to ask an AI assistant to evaluate the environmental impact of electricity usage, travel, freight, cloud computing, procurement and more—all without leaving their conversation context. This capability is especially valuable for organizations that need to embed sustainability metrics into workflows, chatbots, or decision‑support systems.

At its core, the server implements a series of tools that translate natural language prompts into API calls. For example, the electricity‑emission tool accepts a power consumption value and returns the CO₂e emitted, while travel‑emission can handle car, plane or train journeys. More advanced tools such as custom‑emission‑calculation allow the user to plug in specific emission factors, giving fine‑grained control over the calculation. Each tool is accompanied by a resource URI () that stores the full result, making it easy to reference or chain calculations later in a conversation.

The server also offers prompts that generate human‑readable explanations of the calculated impact. The climate‑impact‑explanation prompt can turn a numeric result into an accessible narrative, which is useful for reporting or educational purposes. By combining tools and prompts, developers can build rich conversational experiences where the AI not only performs a calculation but also contextualizes it for the user.

Typical use cases include:

• Sustainability dashboards that automatically fetch and display emissions for corporate travel or energy usage.
• Chat‑based carbon calculators where users can describe their activities in plain language and receive instant feedback.
• Compliance reporting, generating traceable records of emissions that can be referenced in regulatory filings.
• Educational tools that explain climate impact in lay terms, helping users understand the environmental cost of everyday choices.

Integration is straightforward: once the MCP server is running, any AI assistant that supports Model Context Protocol can discover its tools via the standard configuration. The assistant then sends requests in the MCP format, receives a calculation resource, and can prompt the climate‑impact‑explanation to produce a natural language summary—all within a single conversational turn. This tight coupling of data retrieval, computation, and explanation makes the Climatiq MCP Server a powerful addition to any AI‑driven sustainability workflow.