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

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

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

Give Them an Inch and They Will Take a Mile:Understanding and Measuring Caller Identity Confusion in MCP-Based AI Systems

arXiv:2603. 07473v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) is an open and standardized interface that enables large language models (LLMs) to interact with external tools and services, and is increasingly adopted by AI agents.

Cryptographic certificates of validity for trustworthy AI

arXiv:2606. 23768v1 Announce Type: cross Abstract: We propose cryptographic certificates of validity for agentic AI systems.

Bayesian control for coding agents

arXiv:2606. 24453v1 Announce Type: new Abstract: Modern coding agents pair LLM generators with various tools, including cheap diagnostics and expensive verifiers.

Correct Is Not Governed: Provenance Integrity in Agentic Workflows

arXiv:2608. 12761v1 Announce Type: new Abstract: Agentic workflows are commonly evaluated by whether they reach the correct outcome.

A First Look at Coding Agents' Compliance with AI Contribution Rules in Open-Source Communities

Open source communities have been flooded with AI-generated contributions. In defense, they have written contribution rules to regulate coding agents' behavior, spanning from a total ban, mandatory disclosure, to verification gates and human sign-offs.

A First Look at Coding Agents' Compliance with AI Contribution Rules in Open-Source Communities

arXiv:2607. 26819v1 Announce Type: cross Abstract: Open source communities have been flooded with AI-generated contributions.

The Protocol That Cleaned Up Our Agent Architecture

A detailed look at MCP that turned my scattered tool definitions into a stable, discoverable server The post The Protocol That Cleaned Up Our Agent Architecture appeared first on Towards Data Science .

Hybrid Analysis for Secure MCP Tool Use in LLM Agents

arXiv:2607. 25297v1 Announce Type: cross Abstract: The rapid development of large language model (LLM) agents has enabled their broad adoption across diverse real-world tasks.

OpenAgenet/OAN: Technical Architecture for Trust-Governed Agent Identity and Discovery

arXiv:2606. 03163v1 Announce Type: cross Abstract: This paper describes the technical architecture of OpenAgenet / OAN.

Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?

arXiv:2607. 09996v1 Announce Type: new Abstract: Automated failure attribution uses LLMs to identify where and why agentic systems fail.