Tiny Agents in Python: a MCP-powered agent in ~70 lines of code

Tiny Agents: an MCP-powered agent in 50 lines of code

Computer-Using Agent

Building a Multi-Agent System in Python

An introduction to multi-agent systems The post Building a Multi-Agent System in Python appeared first on Towards Data Science .

Introducing smolagents: simple agents that write actions in code.

Holo4: powering generalist computer-use agents

Implementing MCP Servers in Python: An AI Shopping Assistant with Gradio

Give Your Coding Agents a Memory You Own

Introducing AgentKit, new Evals, and RFT for agents

Today, we’re releasing new tools to help developers go from prototype to production faster: AgentKit, expanded evals capabilities, and reinforcement fine-tuning for agents.

New tools for building agents

Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents

Upgrading agentic coding capabilities with the new Devstral models

Can Agents Design Libraries for Agents?

The paper introduces LibraryDesignBench, a benchmark that tests how well agents can design reusable libraries from specifications without prescribed designs. It evaluates libraries by measuring the correctness and simplicity of programs written by three different user agents across 242 programming problems in four languages. Findings show that while agents often replicate human-designed abstractions, downstream agents still tend to reimplement library features due to rigidity or usability issues, and that providing more prescriptive guidance improves reuse and program simplicity.