Kimi Code CLI is Moonshot AI's open-source terminal coding agent, written in TypeScript with subagents and MCP configuration.
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Moonshot AI has open-sourced Kimi K2.7-Code under a Modified MIT license. It is a coding-focused, agentic model built on Kimi K2.6, with a 256K context window and roughly 30% lower reasoning-token usage. Moonshot reports gains over K2.6 on six benchmarks, including +21.8% on Kimi Code Bench v2. The model is available via the Kimi API and Kimi Code.
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Kimi Work's local AI agents could revolutionize productivity by enhancing data privacy and efficiency in complex workflows.
The post Moonshot AI’s Kimi Work unleashes 300 AI agents on your desktop, no cloud required appeared first on Crypto Briefing.
Moonshot AI's Kimi Work is a local desktop agent for macOS and Windows. It runs a 300-sub-agent swarm, drives your logged-in browser via WebBridge, and schedules background jobs.
The post Moonshot AI Launches Kimi Work, a Local Desktop Agent Reportedly Running on Kimi K2.6 With a 300-Sub-Agent Agent Swarm appeared first on MarkTechPost.
Model Context Protocol (MCP) has gained considerable momentum as a standard connector between LLM-powered tools and local systems, internal and external APIs, and data sources. From major clouds to devops tools, MCP servers are enabling powerful, AI-powered development and operations capabilities through natural language commands.
Nowhere is this more true than in the world of databases. Most major database platforms now support agentic access through MCP servers. Using an MCP server for databases, you and your AI agent proxies can perform lookups, create and update data, and perform administrative tasks without you having to write SQL by hand.
The MCP server could also guide your LLMs to write new code or build automations that align with your database schema, like its tables, structure, and fields, as well as embeddings, indexes, and metadata. It could also aid debugging by enabling faster queries to surface data issues or misconfigurations, along with plenty of other possible use ca
By Liam Reid, Senior Product Manager, Legatics. Most law firms now have at least one generative AI tool in production. Many have several. The frontier ...
Enterprises using the lightweight, open-source Flowise platform to power self-hosted AI workloads now have a new near-max-severity issue to worry about.
Researchers at Obsidian Security have detailed a one-click remote code execution (RCE) vulnerability affecting self-hosted Flowise deployments through its implementation of Model Context Protocol (MCP) stdio servers.
The problem is essentially a sandboxing failure of attacker-controlled MCP configurations, leading to server-side code execution.
“Post-auth RCE in Flowise can be triggered with a single click via a malicious chatflow import before any save or run,” the researchers said in a blog post. “The official patch relies on input validation that is trivially bypassed and fails to address the root cause.”
Flowise is commonly used to develop internal AI assistants, retrieval-augmented generation (RAG) applications, customer-facing chatbots, and autonomous agents connected to business systems.
The flaw does not affect Flowise Cloud, a
Nous Research's Hermes Agent adds Tool Search to fix MCP context bloat using BM25 progressive schema disclosure.
The post Hermes Agent Ships Tool Search for MCP: Anthropic Evals Show 49% to 74% Accuracy Gain on Opus 4 appeared first on MarkTechPost.
