InfoWorld AI·
SnapLogic has released MCP Builder, a template-based tool designed to help organizations operationalize AI faster by turning existing integration pipelines into agent-ready Model Context Protocol (MCP) servers. Announced July 1 and generally available in the MCP Server workflow of the SnapLogic platform, MCP Builder generates MCP servers from existing integrations, OpenAPI specifications, and API management services, SnapLogic said. Organizations can publish MCP tools without rebuilding workflows, writing code, or manually constructing MCP implementations, resulting in faster deployment and greater consistency, according to the company. SnapLogic said MCP Builder makes it easier to create MCP Servers, connecting AI agents to trusted enterprise systems and workflows. Unlike DIY MCP approaches, SnapLogic accelerates MCP adoption by turning existing deterministic pipelines into governed MCP tools through a one-step creation experience, while providing enterprise connectivity, identity pr
Read full articleX has unveiled a hosted Model Context Protocol server, giving AI tools such as Claude, Cursor, and Grok Build direct access to the platform through a user’s own account permissions, without requiring developers to build and maintain their own integration infrastructure. The Model Context Protocol is an open standard that defines how AI models communicate […]
St. John's, Antigua and Barbuda, 1st July 2026
X has launched a hosted MCP server, making it easier for developers to connect AI applications with the company’s API.
Microsoft has introduced the Microsoft Binlog MCP Server, which gives AI assistants like GitHub Copilot direct access to MSBuild (.binlog) files. The Model Context Protocol server enables AI-powered build investigation through natural language conversation, Microsoft said. Introduced June 17 and currently in a preview stage, the Microsoft Binlog MCP Server parses .binlog files and exposes 15 specialized tools that enable AI-driven diagnosis, property tracing, performance analysis, and build comparison. Microsoft said that AI assistants gain the ability to do the following: Investigate build failures by querying errors, warnings, and full project/target/task context Trace property origins to understand where a property got its value Analyze performance bottlenecks by identifying the slowest projects, targets, and tasks Compare two builds to spot differences in packages and properties Read embedded source files captured during the build Instead of manually scrolling through the MSBuild
Define a tool once as an MCP server and any MCP-compatible client, any model, any framework, can discover and call it with zero custom integration code per model.
Meta released Astryx, an open-source React design system built on StyleX. It pairs a CSS-variable theme cascade with a CLI and MCP server, so both engineers and AI agents build using the same API. The project is in Beta, MIT-licensed, and grew inside Meta over eight years. The post Meta’s Astryx Brings a CLI and MCP Server to an Open-Source React Design System Agents Can Read appeared first on MarkTechPost.
Enterprises can govern model context protocol (MCP) connections at scale by treating them as part of the agentic AI control plane. Every MCP server, exposed tool, permission, and agent relationship needs ownership, scope, monitoring, and auditability before it supports autonomous work. MCP governance is the discipline of controlling how AI agents discover, select, invoke, and... The post How can enterprises govern MCP connections at scale? appeared first on DataRobot.
In 2025, if you weren’t building with MCP, you weren’t serious about agents. The Model Context Protocol dominated the agent conversation for the better part of the year. Conference talks, roadmaps, hiring plans, all of it revolved around MCP. Then late 2025 into 2026, AI Skills arrived and the backlash was immediate. Engineers declared MCP […]
