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Timestep AI Agents SDK

Welcome! Timestep is a clean, low-level library for building agentic systems using the modern industry standards: A2A (Agent-to-Agent) and MCP (Model Context Protocol) protocols.

Overview

Timestep provides a solid foundation for creating multi-agent systems with clear examples across multiple languages. We follow the Task-generating Agents philosophy from the A2A Protocol, where agents always respond with Task objects that can transition through various states.

Protocols

Timestep is built on two complementary industry standards:

  • A2A Protocol: Agent-to-Agent communication standard for peer-to-peer agent collaboration
  • MCP Protocol: Model Context Protocol for tools, resources, and server-initiated LLM interactions (sampling)

How They Work Together

  • A2A handles agent discovery, task management, and agent-to-agent communication
  • MCP provides tool execution and sampling capabilities
  • Handoffs are implemented using MCP's sampling feature
  • Tool calls are communicated via A2A's input-required task state with a DataPart

First MVP: Handoffs

Our first MVP focuses on handoffs - enabling agents to seamlessly delegate tasks to other specialized agents. This demonstrates the power of combining A2A and MCP.

Prerequisites

  • Python 3.11+ or Node.js 20+
  • OpenAI API key (required for A2A agents using OpenAI)

Quick navigation

Core Features

A2A Integration

  • Task-generating Agents: Always respond with Task objects
  • State management: Tasks transition through states (created, input-required, completed)
  • Tool call communication: Uses input-required state with DataPart for tool calls
  • Agent discovery: Agent Card-based discovery mechanism

MCP Integration

  • Tool execution: MCP tools for agent capabilities
  • Sampling for handoffs: Server-initiated LLM interactions enable agent-to-agent delegation
  • HTTP transport: Streamable HTTP transport for client-server communication

Cross-Language Support

  • Python: Fully functional with working examples
  • TypeScript: Pending MCP SDK v2 release (expected Q1 2026)
  • Web UI: Browser-based chat interface

Packages

Implementation Status

Python

✅ Fully functional - Python implementation is complete and working with handoffs.

TypeScript

⚠️ Pending v2 SDK release - TypeScript implementation is incomplete, pending @modelcontextprotocol/sdk v2 release.