Chaining MCP Tools: Build AI Workflows That Search, Read, Analyze, and Write

NeuroLink: The Universal AI SDK for TypeScript

NeuroLink is a powerful and flexible framework designed to enable developers to build sophisticated AI agents that can interact with various digital systems through the Model-Controller-Presenter (MCP) protocol. This document provides an in-depth guide on how to use NeuroLink to create complex AI workflows, including debugging tips and performance optimization techniques.

Introduction

NeuroLink allows you to connect and orchestrate a wide range of tools, enabling your AI agents to perform tasks such as searching GitHub repositories, querying databases, analyzing data, and posting updates to Slack channels. By breaking down high-level requests into smaller sub-tasks and identifying the appropriate MCP tools for each step, NeuroLink ensures that your AI workflows are efficient and effective.

Example Workflow

Consider an example where you want your AI agent to:

1. Find all recently closed GitHub issues in a repository related to performance.
2. Analyze the resolution steps and any associated code changes.
3. Query a PostgreSQL database for performance data during the resolution period.
4. Draft a summary report on the effectiveness of the fixes and post it to a Slack channel.

Here's how you can achieve this using NeuroLink:

typescript
 
1import { ToolCache,
2
3[Read the full article at DEV Community](https://dev.to/neurolink/chaining-mcp-tools-build-ai-workflows-that-search-read-analyze-and-write-e40)
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