mcp

The tweet discusses the lack of safety mechanisms for irreversible tool calls in AI agents and introduces OrcaRouter's new agent firewall feature that scores tool/MCP calls before execution, while emphasizing the need for independent evaluation.

Mole is a deep research agent for the terminal that uses AI to decompose questions, search sources, and provide answers with verified citations while enforcing budgets and ensuring local data privacy.

A video explains the inner workings of AI agents using the open-source Obsidian plugin Vault Operator as a real example, and announces its 3.5.0 release with a redesigned sidebar and skill registry.

A discussion proposing that AI agents working with production data should use data branches — letting the agent write to a cloned database and then reviewing the final diff instead of approving each action individually.

Agent Plugins is a new open, vendor-neutral standard for packaging Agent Skills and their MCP dependencies into one portable folder, with Google joining as a core maintainer. The article details how the standard simplifies distribution, its manifest requirements, and its compatibility across clients.

MCP-Memory is an open-source MCP server that gives AI agents persistent memory using Google's Open Knowledge Format and SQLite FTS5 for fast retrieval and search.

Introduces the open-source project Loop Engineering, which upgrades prompt engineering into building automated loop systems, providing multiple production-grade patterns and tools, and supporting Claude Code, Codex, etc.

The article introduces the Agent Plugins 1.0.0 specification, which aims to solve the binding and distribution problems between Agent Skills and MCP servers through a standardized portable directory format, and has been adopted by Google, Vercel, and several other companies.

Google Cloud's Agent Plugin lets developers package skills, MCP servers, and tools into a single portable folder, enabling build-once-use-everywhere workflows for AI agents.

OJCP (Open Job Context Protocol) is a new open standard built on MCP that lets AI agents discover, evaluate, and apply to jobs in a structured, consent-first way. It defines schemas and MCP tools for job search, application, and status tracking, aiming to standardize agent-job interactions.

Pillar Security researchers detail Deadbugz, an active supply-chain campaign that distributes a malicious MCP server through GitHub pull requests, gating credential-stealing instructions behind three benign tool calls.

A tinkerer shares custom quality-of-life upgrades for local AI agents, including an MCP broker to reduce context overhead, temporal awareness, context warnings, auto-swapping models, and hybrid memory search with Postgres.

Kent Dodds discusses building Kody Koala to complement big AI labs, noting that it pairs well with Grok Bot via MCP integration.

The tweet shares two internship positions at Alibaba (in reinforcement learning and Code Agent directions), and highlights the open-source terminal AI programming assistant mimofan: built on Rust, supporting Xiaomi MiMo and mainstream large models, with capabilities such as code generation, bug fixing, and automated testing.

Cursor's engineering blog describes how they built a development environment for cloud agents, introducing the anydev CLI and the Cloud Doctor self-healing mechanism, enabling agents to now contribute more than half of merged PRs.

Introducing the open-source web scraping framework Scrapling, which claims to natively bypass protections like Cloudflare, with parsing speed far exceeding BeautifulSoup, built-in StealthyFetcher and CloakBrowser, and support for MCP server integration with AI Agents.

Memoars is an invite-only encrypted memory layer that lets AI assistants share a unified memory via MCP, with client open-sourced and hosted coordinator coming soon.

mcptoon is a zero-dependency Python CLI client for MCP servers that uses a compact TOON format to reduce tool discovery tokens by up to 97%, saving context window space for AI agents.

An opinion piece arguing that AI agents are not killing UI but shifting products toward hybrid interfaces, requiring agent-friendly onboarding alongside human-facing controls for approval, review, and orchestration.

The author announces Sentience Governor, an open-source governance runtime for AI agents that separates declared intent, recorded execution, and retrospective explanation, and checks observed tool activity against declared scope via MCP.