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Constructing an AI-First Interface for Exactly APIs with Mannequin Context Protocol


Over the previous few weeks, I’ve been exploring methods to streamline entry to Exactly’s APIs utilizing AI-first tooling. One promising method has been to leverage the Mannequin Context Protocol (MCP)—an open customary developed by Anthropic—to attach APIs with fashionable massive language mannequin (LLM) interfaces, equivalent to Claude Desktop.

At this time, I’d wish to share a light-weight setup that permits builders—and even non-developers—to work together with our APIs utilizing pure language prompts. This method eliminates the necessity for writing boilerplate code, permitting for intuitive exploration of our providers instantly by means of conversational interfaces.

Constructing an AI-First Interface for Exactly APIs with Mannequin Context Protocol

Why MCP?

MCP affords a standardized technique for AI purposes to attach with APIs, knowledge, and instruments. It gives a structured solution to describe features and parameters, enabling LLMs to dynamically resolve which features to invoke in response to consumer prompts.

This aligns with our broader objective at Exactly: making it simpler to combine high-integrity knowledge with purposes and workflows. With MCP, we scale back the friction concerned in connecting to our APIs, opening new potentialities for fast prototyping and experimentation.

Trusted APIs Powered by AI

To exhibit this, I constructed an MCP server that wraps all of the obtainable endpoints from Exactly APIs. The result’s a code-light atmosphere the place Claude Desktop can execute API calls mechanically based mostly on a consumer’s request—no guide coding required.

The method of wrapping the APIs wasn’t tough, but it surely was detailed. Every endpoint was transformed right into a callable perform MCP may expose. As soon as linked, Claude Desktop can perceive these features and start utilizing them based mostly on consumer directions.

Fast Setup Information

You’ll be able to rapidly stand up and operating with the MCP server. This repository contains the whole lot you want: an inventory of supported API features, detailed set up directions, authentication setup, and pattern requests that can assist you get began.

Key Advantages of an MCP Server

Our MCP server is designed to take away the everyday friction concerned in API integration, providing a easy, scalable bridge between high-quality spatial knowledge and AI interfaces. It helps pure language prompts and permits instantaneous entry to location intelligence instruments and wealthy datasets—with out requiring any code. This lowers the barrier to entry for experimentation and dramatically reduces time-to-value.

Its AI-first design shifts focus away from backend system complexity, permitting groups to focus on fixing real-world challenges. And since it opens API entry to product managers, analysts, and different non-engineering customers, it helps scale the impression of knowledge packages throughout the group—with out including to developer workload. This makes it simpler than ever to show concepts into working options in minutes, not days.

These are only a few examples of the sorts of pure language prompts the MCP server can deal with:

  • “Parse this tackle: John Doe 123 Fundamental St Boston”
  • “Eating places close to 123 Central Ave”
  • “Wildfire danger for 123 Forest Ln”

Whether or not you’re enriching knowledge, exploring location context, or assessing danger, the MCP server makes it straightforward to get solutions immediately—with out writing a single line of code.

Developer portal

Knowledge Integrity Suite Developer Portal

Speed up your developer journey – Our greatest-of-breed APIs empower builders to ship distinctive experiences and groundbreaking purposes on time, each time! With complete documentation and professional help at your fingertips, you’ll have all of the instruments to carry your imaginative and prescient to life.

Finest Practices

The MCP server contains many callable features by default. To enhance efficiency and guarantee mannequin readability, it’s finest to restrict the checklist of obtainable features to solely these wanted in your particular activity. This retains the context lean, and the responses centered.

I hope you get pleasure from attempting out this setup and seeing how straightforward it may be to work together with our APIs utilizing pure language!

When you haven’t already, I additionally encourage you to take a look at our Developer Portal and discover the complete vary of Exactly APIs obtainable. There’s much more you are able to do—and now it’s even simpler to get began.

Joyful constructing!

The publish Constructing an AI-First Interface for Exactly APIs with Mannequin Context Protocol appeared first on Exactly.

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