MCP

An mcp server browser automation setup usually fails the same way: the agent launches a fresh, cookie-less Chromium, hits a login wall, and stalls. NeoBrowser is a Rust MCP server that takes the opposite approach — it drives your installed Google Chrome over CDP and can start already authenticated from your real profile. That is the pitch, and the engineering behind it is real. Whether you should install it today is a harder question, and the answer involves a 404, a disputed differentiator, and four security questions the project’s own launch thread left open. ...

An mcp rest api bridge works by reading your API’s OpenAPI spec at runtime and translating each operation into an MCP tool. You keep the REST API exactly as it is, add a proxy or gateway in front of it, and point your agent at the MCP endpoint. Nothing in the backend is rewritten or redeployed. That is the short answer, and it is genuinely accurate — with one important caveat that the marketing pages bury. “No code changes” describes the API, not the project. You still own a configuration surface, an authentication decision, and a curation judgment call. The teams that get burned are the ones who treat auto-conversion as the finished deliverable instead of step one. ...

Agent CodeMode MCP means letting the script your coding agent writes call the MCP servers your agent has already authenticated. Instead of the model making forty tool calls one at a time, it writes one script; the credential your agent minted is reused from disk. Measured: 40 calls and 262,159 characters become 1 script and 903 characters. What is Agent CodeMode, and why does it exist? Code Mode is the pattern where an LLM writes code that calls tools, instead of calling each tool through the model’s native tool-calling interface. Cloudflare’s Kenton Varda and Sunil Pai named it in September 2025 with a thesis that reads as obvious once you see it: LLMs are better at writing code to call MCP than at calling MCP directly. Anthropic published the same architecture as vendor guidance on November 4, 2025 in Code execution with MCP. The reasoning is about training data: models have seen a very large volume of real TypeScript, and comparatively little synthetic JSON tool-schema blobs. ...

OJCP (Open Job Context Protocol) is a draft open standard that lets AI agents find, read and act on job postings through MCP tools instead of scraping career pages. A provider publishes a manifest at /.well-known/ojcp.json, implements the required search_jobs tool plus five recommended ones, and normalizes its apply paths. Current status: a living v0.2 draft with 80 GitHub stars. Two disambiguations before anything else. First, this OJCP is not Ontario Job Creation Partnerships, the Canadian government program that owns the acronym in most search results; in this article OJCP means the agent-facing job data protocol authored by Recruitics CTO Austin Anderson and governed by a steering committee that includes Workday, CrossCountry Healthcare, Hiring.cafe, aiApply, scale.jobs, LoopCV and Tink. Second, OJCP is not a rival to the Model Context Protocol. The specification says it outright: “OJCP is not a competing protocol. It is a vertical application of MCP for the job data domain.” MCP defines how agents call tools; OJCP defines which tools exist for job search, application and identity verification. ...

Making software extensible software in the age of LLMs is a product-boundary decision before it is a runtime decision. Keep a small, accountable core; put the long tail of one-user requests on an extension point; and give untrusted extension code a narrow capability instead of a credential. The sandbox you choose matters less than the boundary you draw. That is the short version of the argument Jeremy Morrell published on 2026-08-18 in “Extensible software in the age of LLMs”, which reached the Hacker News front page at 177 points and 88 comments the next day (HN item 49363668). This guide turns that essay into a decision process: when to expose an extension point, what to hand it, which isolation primitive fits, and when the answer is that you should not build one at all. ...

Coding agents call MCP servers from scripts by running a CLI (like mcp-call), writing a one-shot script against the MCP SDK over stdio, or letting Code Mode generate code that talks to an HTTP/streamable MCP server. In 2026 you register the server once with claude mcp add or codex mcp add, then your agent’s bash or Python script invokes tools, pipes results through jq, and orchestrates several MCP tools in a single shell flow — instead of burning token budget on dozens of native tool calls. ...

Headless IDA Pro MCP lets AI agents analyze binaries directly through IDA’s decompiler and disassembler without opening the GUI. You set up IDA Pro 9.4, expose idalib through a Rust-native MCP server such as ida-mcp-rs, connect it to Claude Code or Cursor, and then drive decompilation, xrefs, renames, comments, and scripting through natural language. In 2026 this workflow is faster to stand up, more memory-safe, and far more capable than the Python MCP servers of a year earlier. ...

Sallyport is a free Mac app that holds your API and SSH credentials in an encrypted local vault and executes authenticated actions for your AI agents over MCP. The agent gets the operation, never the key: there is no command that reveals a stored credential and no export route. It runs entirely on your Apple Silicon Mac, gated by Secure Enclave and Touch ID, with no account, cloud, or telemetry. ...

Apple’s Safari MCP server, released July 1, 2026 in Safari Technology Preview 247, is the first official browser MCP integration from a major browser vendor. It lets any MCP-compatible AI agent connect to Safari and read the DOM, capture screenshots, evaluate JavaScript, inspect network traffic, and manage tabs — turning the terminal into a full WebKit debugging surface. This guide walks through enabling remote automation, configuring Claude Code and Codex, the 16 built-in tools, and the security trade-offs you need to know before letting an agent touch your browser. ...

Cove Sensory MCP is a local stdio MCP server that hands text-only LLMs like Claude Code and Codex their missing senses: image, video, audio, and music understanding. It routes media files through configurable multimodal providers—Gemini, MiniMax-M3, or OpenAI-compatible endpoints—while keeping everything on-device and privacy-first. Rather than a full assistant, it is a composable sensory layer you bolt onto your existing agent. H2: What Is Cove Sensory MCP and Why a “Sensory Layer”? Cove Sensory MCP is a Model Context Protocol server that deliberately limits itself to a single job: giving text-only language models the ability to perceive media files. The concept comes from Anthropic’s Model Context Protocol, a universal open standard that lets AI applications connect to external tools and context. Instead of trying to build chat, memory, personality, playback, monitoring, or call policies, Cove’s creators carved out one focused capability—sensing—and made it reusable across agents. ...