What it is: MongoDB Atlas now delivers cost and usage data in the FinOps Open Cost and Usage Specification (FOCUS) v1.3 format. This capability offers industry‑standard billing datasets with detailed attributes for each line item — such as currency, applied discounts, credit allocations, account and project mappings, and SKU categories.Who it’s for: Atlas Organization Owners, Billing Admins, and Billing Viewers — particularly in enterprise organizations managing complex, programmatic cost allocations across multiple cloud and SaaS vendors.Why it matters: This launch aligns Atlas billing data with a widely adopted cloud reporting standard, simplifying integration into unified FinOps reporting pipelines and eliminating the need for custom SKU mapping. It also introduces additional billing attributes for greater insight and transparency, enabling faster, clearer, and more consistent cross‑vendor spend monitoring and cost analysis.How to get started: Retrieve FOCUS‑formatted billing data directly through the Atlas Admin API or download it from the Atlas billing UI. See the Atlas documentation for more information.

What it is: MongoDB is now available as a native plugin in the marketplaces and connector directories of popular AI clients — including Claude, ChatGPT, Cursor, Devin, and Grok Build — backed by the MongoDB Atlas Managed MCP Server, a MongoDB-hosted Model Context Protocol (MCP) server. Each marketplace plugin packages the managed MCP server connection together with MongoDB agent skills, so an AI client gains both the tools to query and manage Atlas resources and the guidance to use them well, with no MCP infrastructure to host, configure, or maintain. Who it's for: This is for developers already working in AI clients such as Claude, ChatGPT, Cursor, Devin, and Grok Build who want to query, explore, and manage data in MongoDB Atlas in natural language without leaving their tool or setting up a local MCP server. It also serves Atlas administrators who need AI access to be governed, auditable, and revocable at the organization level. Why it matters: Connecting an AI client to MongoDB Atlas goes from a manual setup project — hosting a local MCP server, copying connection strings, rotating credentials — to finding MongoDB in the tool's marketplace and authorizing access with a single OAuth consent. Agent actions are attributed to the individual user who authorized it, and administrators retain control through org-level enablement and optional read-only enforcement; AI client access is disabled by default. How to get started: Click the documentation link below for a step-by-step guide on how to get started with the MongoDB Atlas Managed MCP Server in your preferred AI client.

What it is: voyage-code-4 is our next-generation code embedding model, purpose-built to improve retrieval quality and reduce costs for coding agents, supporting flexible dimensions (2048, 1024, 512, and 256) along with float32, int8, and binary quantization.Who it's for: This model is for teams building coding agents, code assistants, and code search applications over large, real-world repositories.Why it matters: Most coding agents today rely on full-text search (i.e., grep), which fails when a query describes a symptom rather than syntax; semantic retrieval with voyage-code-4 complements full-text search and significantly reduces wasted token usage, outperforming Cohere Embed v4 and Gemini Embedding 2 by 28.25% and 31.03% on agentic code retrieval at $0.12 per 1M tokens (a third below the price of voyage-code-3).How to get started: Sign up, generate a model API key, and get 200M free tokens on our latest models, then dive into the quick start to start building with voyage-code-4.