waldzellai

Mcp Agent Ts

Name: Mcp Agent Ts
Author: waldzellai

AI community

SOURCE https://github.com/waldzellai/mcp-agent-ts

Description

TypeScript port of the original MCP Agent framework by lastmile-ai

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

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MCP Agent TypeScript Port

[![smithery badge](https://smithery.ai/badge/@waldzellai/mcp-agent-ts)](https://smithery.ai/server/@waldzellai/mcp-agent-ts)

Overview

The MCP (Model Context Protocol) Agent TypeScript Port is a robust type-safe implementation of the MCP Agent system. It provides a flexible framework for building intelligent context-aware agents with advanced workflow management, logging, and execution capabilities.

This is a TypeScript port of the [original MCP Agent framework by lastmile-ai](https://github.com/lastmile-ai/mcp-agent).

Features

🚀 **Modular Architecture**
- Comprehensive TypeScript implementation
- Flexible, extensible design
- Type-safe interfaces
📊 **Advanced Workflow Management**
- Step-based workflow execution
- Concurrent task processing
- Detailed context tracking
🔍 **Powerful Logging System**
- Configurable log levels
- Context-rich logging
- Log export capabilities
🧰 **Flexible Executor**
- Task queuing
- Timeout handling
- Concurrent task management
🖥️ **CLI Support**
- Command-line interface
- Easy agent management

Installation

Installing via Smithery

To install MCP Agent TypeScript Port for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@waldzellai/mcp-agent-ts):

npx -y @smithery/cli install @waldzellai/mcp-agent-ts --client claude

Manual Installation

npm install @waldzell/mcp-agent-ts

Quick Start

Creating a Workflow

import { BaseWorkflow } from '@waldzell/mcp-agent-ts';

class MyDataProcessingWorkflow extends BaseWorkflow {
  constructor() {
    super('my-workflow', 'Data Processing');

    this.addStep({
      id: 'extract',
      name: 'Data Extraction',
      execute: async (context) => {
        // Implement data extraction logic
        r