Conduit FAQs

Question 1

What is Conduit and what problem does it solve?

Accepted Answer

Conduit is a lightweight microservice that automates exposing any GraphQL API as consumable tools for Large Language Models (LLMs) via the Model Context Protocol (MCP). It eliminates manual tool definition, bridging the gap between your API and AI agents.

Question 2

How does Conduit handle updates to my GraphQL API?

Accepted Answer

Conduit offers 'Zero-Maintenance' operation. It automatically discovers your API's capabilities (queries, mutations) using introspection. When your API updates, Conduit automatically reflects these changes without any manual intervention.

Question 3

What is the Model Context Protocol (MCP) and why is it important?

Accepted Answer

The Model Context Protocol (MCP) is a standard that allows LLMs to interact with external tools and services. Conduit is 'Protocol Compliant,' implementing core MCP endpoints like `/listTools`, `/getToolSchema`, and `/executeTool` for seamless LLM integration.

Question 4

How does Conduit execute LLM tool calls?

Accepted Answer

Conduit features 'Dynamic Execution,' meaning it translates LLM tool calls into valid GraphQL queries or mutations and executes them against your GraphQL API. This enables LLMs to interact with your backend services effectively.

Question 5

Is Conduit easy to deploy?

Accepted Answer

Yes, Conduit is 'Container-Ready.' It includes a Dockerfile and Kubernetes manifests, making it straightforward to deploy as a stateless microservice alongside your existing infrastructure.

Conduit

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Key Features

Use Cases

Key Features

Use Cases