MCP

MCP makes tools callable by agents. That solves invocation. It does not solve visibility. The next agent and the next human still need to see what the tool calls produced, and a transcript is the wrong place for that.

Skills gave an agent what to know. The missing half is what role to play. Agent Studio lets you author subagents next to your skills in one place, serve both over the same MCP endpoint with the same progressive disclosure, browse them over REST and the dd CLI, and publish them to the community under a moderation loop. Here is the design and why the two belong in one studio.

Skills, files, memory, and generation do not need four integrations. They need one MCP endpoint with tiered disclosure, one API key that scopes everything to its owner, and one credit balance. The same tools answer to an MCP client, an in-product chat, and a CLI. Here is the whole architecture, and why it is the shape that makes a fleet of agents coherent.

A decision framework for 2026: MCP servers give an agent access to a live system, Agent Skills teach it how to do a task. Here is when to build each, when to build both, and the criteria that actually decide it, grounded in the MCP spec and Anthropic's skills docs.

The first version of skills-over-MCP served a fixed first-party catalog. Skill Studio extends it two ways: anyone can author skills that ride the same progressive-disclosure endpoint scoped to their own API key, and a skill file can be a link instead of a copy - a URL whose bytes are only fetched at the moment an agent decides it needs them. Progressive disclosure stops at the skill boundary no longer. It runs out to the open web.

The 2026-07-28 Model Context Protocol spec is the largest revision since launch: a stateless core, deprecated Roots/Sampling/Logging, MCP Apps, Tasks, and tougher OAuth. Here is what breaks, what to adopt, and a migration checklist for server authors and client integrators before the July 28 deadline.

developersdigest.tech now speaks MCP. Any MCP-capable harness can call the site's tools directly - generate media, pull vetted skills and agents on demand, persist memory across sessions, search the content, and count tokens. Here is what shipped and how to connect.

SKILL.md solved knowledge packaging with progressive disclosure. MCP solved capability transport but ships flat, context-hungry tool lists. The next shape combines them - an MCP server whose tools are a skill directory, so an agent pays context only for what the task needs. Here is the argument and a working implementation.

A hosted infinite canvas your headless AI agents drive over MCP. Any MCP-speaking agent - Claude Code, Codex, Cursor, or a script - creates HTML docs, images, and video on a live canvas, streamed in as it builds.

Bumblebee is Perplexity's open source scanner for detecting compromised packages, extensions, and MCP configs on developer machines. A read-only Go binary that checks npm, PyPI, Go modules, and 10+ ecosystems against exposure catalogs - without running any install scripts. Here is how to set it up and use it.

Arcade just raised $60M to become the secure action layer for production AI agents. Here is what their MCP runtime actually does, how it differs from rolling your own OAuth, and when to use it.

The Linux Foundation's Agent Name Service proposal points at a real gap in AI agent infrastructure: agents need verifiable identity, scoped capabilities, revocation, and audit trails before they can safely act across tools.

GitHub's Agent Finder discovers and invokes Claude, Codex, MCP servers, and skills automatically. Here is how the new ARD specification changes AI coding tool integration.

The MCP 2026-07-28 final spec is here - sessions are gone, the protocol is stateless. Here is what changed, what broke, and how to finish migrating your MCP servers.

MCP's new enterprise-managed authorization flow is not just less login friction. It moves agent tool access into identity, policy, and audit systems enterprises already understand.

MCP's new Enterprise-Managed Authorization removes per-user OAuth friction. Anthropic, Okta, Figma, and Linear ship centralized auth for AI agent tooling.

JetBrains released Mellum2 on June 2, 2026 - a 12B MoE model with only 2.5B active parameters per token. Here is how to run it locally, when to use it, and where it fits in your AI coding stack.

On June 2, 2026, GitHub made the Copilot SDK generally available. It exposes the same agent runtime behind Copilot - planning, tool calls, file edits, streaming, MCP - across TypeScript, Python, Go, .NET, Rust, and Java. Here is what changed at GA and what it means for builders.

On June 16, 2026, Microsoft's Work IQ APIs reach general availability - a workplace intelligence layer that hands agents pre-assembled, permission-trimmed Microsoft 365 context instead of raw Graph calls. Here is what the four domains, three protocols, and consumption pricing mean for developers building enterprise agents.

OpenCode is the fastest-growing open-source AI coding agent - 160K GitHub stars, 7.5M monthly users, 75+ model providers. Here is how to set it up, configure models, and use it effectively in your workflow.