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Copilot CLI 0.0.406 adds MCP upgrades and Claude preview; community proxy unlocks Copilot in Cursor

GitHub Copilot CLI 0.0.406 brings MCP-focused UX improvements, a Claude Opus 4.6 Fast preview, and safer flags, while a community proxy shows how to use a Copilot subscription inside Cursor’s Agent features. Per the official notes, v0.0.406 adds Claude Opus 4.6 Fast support, command-to-skill translation, /changelog, MCP status, structured responses for VS Code, URL-based plugin marketplace, and a --no-experimental flag [GitHub Copilot CLI releases](https://github.com/github/copilot-cli/releases)[^1]. A community guide details a "Copilot Proxy for Cursor" that routes Cursor to your Copilot key with MCP/tool support and vision handling; use cautiously given it relies on internal APIs [DEV: Unlock GitHub Copilot in Cursor](https://dev.to/jacksonkasi/unlock-github-copilot-in-cursor-the-ultimate-guide-free-unlimited-4i9c)[^2]. [^1]: Adds: Official 0.0.406 features, MCP/skills changes, and safety flags. [^2]: Adds: How the proxy works, setup steps, supported models/tools, and caveats.

calendar_today 2026-02-07
github-copilot github copilot-cli cursor anthropic

VS Code Copilot Chat v0.38 (pre-release): Claude GA, memory tool, and CLI integration updates

VS Code Copilot Chat v0.38 (pre-release) introduces Claude graduating from preview, Anthropic memory tooling (including local memory), a rename of /summarize to /compact with optional instructions, and Copilot CLI integration migration. See the extension’s pre-release notes for Anthropic memory tool support and checks, Claude graduation, /summarize ➜ /compact, subagent improvements, hooks stopReason/warningMessage, telemetry fixes, and the Copilot CLI integration migration [release notes](https://github.com/microsoft/vscode-copilot-chat/releases)[^1]. For enterprise enablement and procurement, this guide outlines how to subscribe to GitHub Copilot via Azure [implementation path](https://medium.com/@addozhang/subscribing-to-github-copilot-via-azure-enterprise-ai-programming-assistant-implementation-path-2504adeff1d8)[^2]. [^1]: Adds: Official v0.38 pre-release changelog with specific features and fixes. [^2]: Adds: Enterprise subscription route via Azure for rolling out Copilot.

calendar_today 2026-02-07
vs-code-copilot-chat github-copilot copilot-cli claude claude-code

Mixture-of-Models router tops single LLMs on SWE-Bench Verified (75.6%)

A lightweight router that clusters tasks and selects the historically best model per cluster hit 75.6% on SWE-Bench Verified, narrowly outperforming top single-model baselines (~74%). Details and methodology are outlined in Nordlys Labs' write-up, including semantic clustering and per-cluster success routing without test-time search or repo execution [Nordlys Labs blog](https://nordlyslabs.com/blog/hypernova)[^1]. The open-source framework implementing this mixture-of-models approach is available here [Nordlys GitHub](https://github.com/Nordlys-Labs/nordlys)[^2]. [^1]: Adds: methodology, routing design, and reported benchmark results. [^2]: Adds: production-ready code for the router and integrations.

calendar_today 2026-02-07
nordlys-labs nordlys swe-bench swe-bench-verified llm-routing

Claude Code Opus 4.6 adds Fast mode and native Agent Teams

Claude Code now ships Fast mode for Opus 4.6 and native Agent Teams, plus a hotfix that makes /fast immediately available after enabling extra usage. Release notes confirm Fast mode for Opus 4.6 and the /fast availability fix, with setup docs for toggling and usage [here](https://github.com/anthropics/claude-code/releases)[^1] and [here](https://code.claude.com/docs/en/fast-mode)[^2]. Walkthroughs show how to stand up Agent Teams and add lightweight persistent memory so the agent keeps project context across sessions [here](https://www.youtube.com/watch?v=QXqnZsPLix8&pp=ygUSQ2xhdWRlIENvZGUgdXBkYXRl0gcJCZEKAYcqIYzv)[^3] and [here](https://www.youtube.com/watch?v=ryqpGVWRQxA&pp=ygUSQ2xhdWRlIENvZGUgdXBkYXRl)[^4]. [^1]: Adds: official v2.1.36/37 release notes (Fast mode enabled for Opus 4.6; /fast availability fix) and prior sandbox bug fix. [^2]: Adds: official Fast mode documentation and guidance. [^3]: Adds: hands-on demo and setup steps for native Agent Teams in Claude Code V3. [^4]: Adds: tutorial to implement persistent memory so Claude retains codebase context.

calendar_today 2026-02-07
anthropic claude-code claude-opus-46 fast-mode agent-teams

GitHub plans PR controls as AI code floods repos; tame API sprawl before rolling out agents

GitHub is evaluating stricter pull request permissions and AI-based filters (e.g., collaborators-only PRs, disabling PRs for mirrors) to curb the surge of low-quality, AI-generated contributions overwhelming maintainers ([InfoWorld](https://www.infoworld.com/article/4127156/github-eyes-restrictions-on-pull-requests-to-rein-in-ai-based-code-deluge-on-maintainers.html)[^1]). For backend teams deploying agents, unchecked API sprawl breaks autonomy, contracts, and observability—causing silent data pollution and reliability issues unless a governed API catalog and clear schemas are in place ([Nordic APIs](https://nordicapis.com/how-api-sprawl-cripples-your-ai-strategy-and-how-to-fix-it/)[^2]). Small, auditable AI-assisted scripts can deliver value (e.g., a 400-line Python log colorizer built with Claude Code) but don’t scale the review burden or governance needs of larger codebases ([Ars Technica](https://arstechnica.com/features/2026/02/so-yeah-i-vibe-coded-a-log-colorizer-and-i-feel-good-about-it/)[^3]). [^1]: Adds: Specific PR controls GitHub is considering and community feedback on AI-driven PR quality. [^2]: Adds: Concrete failure modes from API sprawl for agentic AI (discovery, contract drift, observability, security). [^3]: Adds: Real-world, small-scope AI-assisted dev example and its auditability/scale trade-offs.

calendar_today 2026-02-04
github github-copilot claude-code claude python

Codex 0.95–0.96 ship async compaction, rate-limit signals; MassGen adds Codex backend

OpenAI’s Codex app/server shipped 0.95–0.96 with v2 async thread compaction, websocket rate‑limit signaling, expanded skill loading/remote catalogs, shell parallelism, state‑DB correctness, telemetry, and Linux sandbox groundwork ([0.95.0](https://github.com/openai/codex/releases/tag/rust-v0.95.0)[^1], [0.96.0](https://github.com/openai/codex/releases/tag/rust-v0.96.0)[^2]). MassGen now offers a Codex backend with local/Docker modes to orchestrate multi‑agent workflows and MCP tooling ([MassGen v0.1.47](https://github.com/massgen/MassGen/releases/tag/v0.1.47)[^3]). Expect workflow differences vs IDEs—Codex is positioned as an agentic assistant, not a full IDE—and note a Windows PowerShell 5.1 ANSI‑encoding issue affecting Cyrillic output ([video](https://www.youtube.com/watch?v=ts7yQdfBW_U&pp=ygURQ3Vyc29yIElERSB1cGRhdGU%3D)[^4], [forum thread](https://community.openai.com/t/incorrect-cyrillic-rendering-in-codex-agent-on-windows-due-to-powershell-5-1-default-ansi-encoding/1356123#post_5)[^5]). [^1]: Release notes: skills loading and remote catalogs, macOS `codex app` CLI, shell parallelism, Git safety hardening, TUI improvements, Linux sandbox groundwork. [^2]: Release notes: `thread/compact` async RPC, websocket `codex.rate_limits` event, `unified_exec` enablement, state DB-first thread listing, telemetry. [^3]: MassGen adds a Codex backend (local/Docker), native tool architecture, and a quick start to try Codex workflows. [^4]: Explains Codex app’s agentic workflow vs IDEs like Cursor and how to use it effectively. [^5]: Documents Windows PowerShell 5.1 ANSI encoding causing Cyrillic rendering issues and workaround considerations.

calendar_today 2026-02-04
openai codex massgen cursor claude-code

Mixture-of-Models routing tops single LLMs on SWE-Bench via task specialization

A lightweight Mixture-of-Models router that assigns issues to semantic clusters and routes to the historically strongest model per cluster hit 75.6% on SWE-Bench, edging past single-model baselines (~74%) by exploiting complementary strengths rather than defaulting to the top aggregate model [Reddit summary](https://www.reddit.com/r/LocalLLaMA/comments/1qvm0ft/mixtureofmodels_routing_beats_single_llms_on/)[^1]. The authors share a methodology write-up and an open-source framework so teams can reproduce the gating approach without test-time search or repo execution [methodology blog](https://nordlyslabs.com/blog/hypernova)[^2] and [framework code](https://github.com/Nordlys-Labs/nordlys)[^3]. [^1]: Highlights task-level specialization on SWE-Bench and the routing approach with reported results. [^2]: Details the clustering, per-model success statistics, and routing mechanism. [^3]: Provides the open-source implementation for building a MoM router.

calendar_today 2026-02-04
nordlys nordlys-labs swe-bench mixture-of-models model-routing

Copilot January: agents in VS Code, VS UX boosts, and CLI ACP/MCP updates

GitHub is pushing Copilot deeper into agent workflows: VS Code v1.109 adds multi‑agent session management, Claude agent support, MCP‑powered tool integrations, memory/indexed code search, and terminal command sandboxing, while Visual Studio gains colorized and partially‑acceptable completions plus Markdown preview improvements ([changelog](https://github.blog/changelog/2026-02-04-github-copilot-in-visual-studio-code-v1-109-january-release/)[^1], [VS update](https://github.blog/changelog/2026-02-04-github-copilot-in-visual-studio-january-update/)[^2]). On the CLI, v0.0.402 ships ACP server agent/plan modes, plugin lifecycle fixes, and MCP server cleanup, alongside a community request for a post‑update "What’s New" summary; GitHub’s tutorial shows how to add custom instructions and a copilot‑setup‑steps workflow so agents can safely improve mature repos ([release](https://github.com/github/copilot-cli/releases/tag/v0.0.402)[^3], [issue](https://github.com/github/copilot-cli/issues/1277)[^4], [tutorial](https://docs.github.com/en/copilot/tutorials/coding-agent/improve-a-project)[^5]). [^1]: Adds: VS Code changelog with multi‑agent management, Claude agent preview, MCP integrations, memory/indexing, and terminal sandboxing. [^2]: Adds: Visual Studio update detailing colorized completions and partial acceptance UX. [^3]: Adds: Copilot CLI v0.0.402 notes on ACP modes, plugin lifecycle, and MCP server shutdown. [^4]: Adds: Community feature request to show a concise post‑update "What’s New" in Copilot CLI. [^5]: Adds: Official guide to using Copilot coding agent with custom instructions and setup steps in repos.

calendar_today 2026-02-04
github github-copilot visual-studio visual-studio-code anthropic

Claude Code 2.1.x lands practical speedups and governed multi‑agent workflows

Anthropic pushed a rapid series of Claude Code 2.1 updates (v2.1.26–v2.1.31) that cut RAM on session resume, add page‑level PDF reads, support MCP servers without dynamic registration, enable PR‑based session bootstraps, and ship many reliability fixes [Reddit summary](https://www.reddit.com/r/ClaudeAI/comments/1qvgdc5/claude_code_v21262130_what_changed/)[^1] and [official v2.1.31 notes](https://github.com/anthropics/claude-code/releases/tag/v2.1.31)[^2]. Practitioners also highlight 2.1’s skill hot‑reload, lifecycle hooks, and forked sub‑agents as a foundation for governed, observable multi‑agent workflows—positioning Claude Code as a lightweight "agent OS" for real projects [deep dive](https://medium.com/@richardhightower/build-agent-skills-faster-with-claude-code-2-1-release-6d821d5b8179)[^3]. [^1]: Adds: community changelog for v2.1.26–30 covering performance, MCP, GitHub/PR workflows, and PDF handling. [^2]: Adds: official v2.1.31 fixes (PDF lockups, sandbox FS errors, streaming temperature override, tool routing prompts, provider labels) and hard limits (100 pages, 20MB). [^3]: Adds: perspective on skill hot‑reload, lifecycle hooks, and forked sub‑agents enabling governed multi‑agent patterns.

calendar_today 2026-02-04
claude-code anthropic mcp-model-context-protocol github slack

MassGen v0.1.46 released

MassGen v0.1.46 is out — review the official GitHub release page before upgrading to ensure compatibility with your pipelines and tooling [MassGen v0.1.46 release](https://github.com/massgen/MassGen/releases/tag/v0.1.46)[^1]. For safety, stage the upgrade behind a canary/feature flag and compare outputs and logs between your current version and v0.1.46 to catch regressions early. [^1]: Adds: official release page with version details and assets.

calendar_today 2026-02-03
massgen github release-management ci-cd sdlc

Continue config-yaml 1.41–1.42 expands model routing, hardens CLI/networking

Continue shipped config-yaml updates that add OpenRouter dynamic model loading and Nous Research Hermes models, plus SSL verification for client transports and reasoning-content handling in chats ([config-yaml 1.42.0](https://github.com/continuedev/continue/releases/tag/%40continuedev/config-yaml%401.42.0)[^1]). The prior release fixes OpenAI Responses API parallel tool-call call_ids, improves WSL PATH detection, patches file-descriptor leaks in resource monitoring, upgrades openapi-generator, and adds .continuerc.json tool prompt overrides ([config-yaml 1.41.0](https://github.com/continuedev/continue/releases/tag/%40continuedev/config-yaml%401.41.0)[^2]). A separate CLI stable build was published directly from main ([CLI v1.5.43](https://github.com/continuedev/continue/releases/tag/v1.5.43)[^3]); note the Feb 3 config changes may land in a subsequent CLI cut. [^1]: Adds: OpenRouter provider, Hermes models, SSL verification toggle, and reasoning-content support. [^2]: Adds: Responses API call_ids fix, WSL PATH detection, resource monitoring stability, tool prompt overrides. [^3]: Adds: Stable CLI build note; timing suggests it may not include Feb 3 config-yaml changes.

calendar_today 2026-02-03
continue continue-cli openrouter openai nous-research

Continue CLI beta ships daily with 7-day promote-to-stable cadence

The Continue CLI daily beta v1.5.43-beta.20260203 is out on [GitHub](https://github.com/continuedev/continue/releases/tag/v1.5.43-beta.20260203)[^1], with a policy to promote to stable after 7 days if no critical issues are found. This cadence lets teams canary the beta in CI, pin a version, and be ready to roll forward (or back) around the promotion window. [^1]: Adds: release availability, daily beta cadence, and 7-day promotion policy details.

calendar_today 2026-02-03
continue github cli release-management ci-cd

E2E coding agents: 27% pass, cheaper scaling, and safer adoption

A new end-to-end benchmark, [ProjDevBench](https://arxiv.org/html/2602.01655v1)[^1] with [code](https://github.com/zsworld6/projdevbench)[^2], reports only 27.38% acceptance for agent-built repos, highlighting gaps in system design, complexity, and resource management. Efficiency is improving: [SWE-Replay](https://quantumzeitgeist.com/17-4-percent-performance-swe-replay-achieves-gain-efficient/)[^3] recycles prior agent trajectories to cut test-time compute by up to 17.4% while maintaining or slightly improving fix rates. For evaluation and safety, Together AI shows open LLM judges can beat GPT‑5.2 on preference alignment ([post](https://www.together.ai/blog/fine-tuning-open-llm-judges-to-outperform-gpt-5-2at/))[^5], Java teams get a pragmatic path via [ASTRA‑LangChain4j](https://quantumzeitgeist.com/ai-astra-langchain4j-achieves-llm-integration/)[^6], and an open‑weight coding LM targets agentic/local dev ([Qwen3‑Coder‑Next](https://www.youtube.com/watch?v=UwVi2iu-xyA&pp=ygURU1dFLWJlbmNoIHJlc3VsdHM%3D))[^7]. [^1]: Adds: defines an E2E agent benchmark with architecture, correctness, and refinement criteria plus pass-rate findings. [^2]: Adds: benchmark repository for tasks, harnesses, and evaluation assets. [^3]: Adds: test-time scaling via trajectory replay with up to 17.4% cost reduction and small performance gains on SWE-Bench variants. [^4]: Adds: DPO-tuned open "LLM-as-judge" models outperform GPT‑5.2 on RewardBench 2 preference alignment, with code/how-to. [^5]: Adds: security analysis of self-propagating adversarial prompts ("prompt worms") and the OpenClaw agent network example. [^6]: Adds: Java integration pattern for agent+LLM via ASTRA modules and LangChain4J, including BeliefRAG and Maven packaging. [^7]: Adds: open-weight coding model positioned for agentic workflows and local development.

calendar_today 2026-02-03
projdevbench swe-replay swe-bench-verified swe-bench-pro astra

CORE: Persistent memory and actions for coding agents via MCP

CORE is an open-source, self-hostable memory agent that gives coding assistants persistent, contextual recall of preferences, decisions, directives, and goals, and can trigger actions across your stack via MCP and app integrations like Linear, GitHub, Slack, Gmail, and Google Sheets; see [CORE on GitHub](https://github.com/RedPlanetHQ/core)[^1]. For backend/data teams, this replaces brittle context-dumps with time- and intent-aware retrieval across Claude Code and Cursor, enabling consistent code reviews and automated updates tied to prior decisions. [^1]: Adds: repo, docs, and integration details (MCP, supported apps, memory model, self-hosting).

calendar_today 2026-02-03
core redplanethq claude-code cursor mcp

OpenAI Codex ships macOS app with parallel agents, Plan mode, and higher limits

OpenAI released a macOS Codex app that runs parallel agent threads for long‑running work with built‑in Git/worktrees, skills, automations, and temporarily higher rate limits across app/CLI/IDE for paid tiers ([Codex changelog](https://developers.openai.com/codex/changelog/)[^1]). The latest release enables Plan mode by default, stabilizes personality config, supports loading skills from .agents/skills, and surfaces runtime metrics for diagnostics ([v0.94.0 release](https://github.com/openai/codex/releases/tag/rust-v0.94.0)[^2]). OpenAI is positioning Codex for autonomous, multi‑threaded, complex tasks vs. Claude Code, citing 1M monthly users and 20x growth since August, while community reports mention a large context window (unconfirmed) ([Sources newsletter](https://sources.news/p/openai-takes-aim-at-anthropics-coding)[^3], [Reddit thread](https://www.reddit.com/r/OpenAI/comments/1qu7hii/openai_just_massdeployed_codex_to_every_surface/)[^4]). [^1]: Official feature overview and rate-limit details. [^2]: Release notes (Plan mode default, skills folder support, personality, metrics). [^3]: Press briefing recap with positioning vs. Claude Code and usage stats. [^4]: Community summary noting "trinity" surfaces and context-size claim (unverified).

calendar_today 2026-02-03
openai codex chatgpt anthropic claude-code

Copilot SDK + MCP: From visual bugs to auto-PRs, now easier to wire into your stack

GitHub is turning Copilot into an embeddable agent host: the new Copilot SDK lets you run a headless, CLI-backed agent with MCP registry support inside your own apps and services, enabling remote, licensed users to leverage the same orchestration loop programmatically ([InfoWorld](https://www.infoworld.com/article/4125776/building-ai-agents-with-the-github-copilot-sdk.html)[^1], [Microsoft Dev Community](https://techcommunity.microsoft.com/blog/azuredevcommunityblog/the-perfect-fusion-of-github-copilot-sdk-and-cloud-native/4491199)[^2]). On the workflow side, Copilot CLI v0.0.401 improves MCP tool output handling (structuredContent), adds auto-loading skills, and other stability upgrades, while GitHub’s best practices detail instruction files, tool allowlists, and model selection for safer automation ([GitHub release](https://github.com/github/copilot-cli/releases/tag/v0.0.401)[^3], [Copilot CLI best practices](https://docs.github.com/en/copilot/how-tos/copilot-cli/cli-best-practices)[^4]). Practically, teams can feed Copilot richer context—images in issues/Chat and MCP-bridged telemetry from bug capture tools—to turn visual reports into targeted fixes and PRs ([Provide visual inputs](https://docs.github.com/en/enterprise-cloud@latest/copilot/how-tos/use-copilot-agents/coding-agent/provide-visual-inputs)[^5], [Reddit example](https://www.reddit.com/r/GithubCopilot/comments/1qu4lck/using_mcp_to_turn_visual_bug_reports_into_instant/)[^6]). [^1]: Adds: Explains how the Copilot SDK embeds a headless CLI-backed agent with MCP registry and remote usage details. [^2]: Adds: Positions the SDK in multi-agent/cloud-native patterns and notes technical preview posture and capabilities. [^3]: Adds: Lists v0.0.401 improvements, including MCP structuredContent rendering and auto-loading skills. [^4]: Adds: Prescribes instruction files, allow/deny tool policies, and operational tips for CLI usage. [^5]: Adds: Shows how to attach images to issues/Chat so Copilot can create PRs from visual specs. [^6]: Adds: Real-world MCP bridge pattern that pulls bug data (DOM, console, network) into Copilot to propose fixes.

calendar_today 2026-02-03
github-copilot github-copilot-cli github-copilot-sdk model-context-protocol-mcp github

GitHub Copilot: GPT-5.1 Codex preview, Spaces sharing, and model retirements

GitHub Copilot added a public preview of GPT-5.1-Codex-Max across web, IDE, mobile, and CLI (Enterprise/Business must enable it), made Spaces shareable publicly or per-user with a code-viewer add-to-Space flow, and refined the VS model picker. Older OpenAI/Anthropic/Google models were retired with suggested replacements, agents gained mission control and skills with broader IDE coverage, and knowledge bases fully sunset in favor of Spaces.

calendar_today 2026-01-06
github-copilot agentic-ai context-grounding model-lifecycle jetbrains

Pair Qodo (PR/CI) with Windsurf (IDE) for AI-driven code quality

Qodo positions itself as the AI code review and test/coverage gatekeeper for PRs and CI (Qodo Merge/Gen/Cover), with on‑prem/VPC options, SOC 2 Type II, and zero data retention. Windsurf (by Codeium) focuses on agentic coding in the IDE (autocomplete, multi-file edits), with basic GitHub-only PR review in beta and chat-driven test generation but no dedicated coverage feature. The pitch is to let Windsurf generate code while Qodo enforces standards and coverage before merge.

calendar_today 2026-01-06
qodo windsurf code-review test-generation ci-cd

Drop-in memory for Claude Code: persist context across sessions

A community-made Claude Code skill (ensue-memory) adds a lightweight memory DB to persist session context and provide semantic/temporal recall between sessions, reducing repeated setup and reminders. It's alpha and unofficial; discussion notes trade-offs with model-side compaction and the chance native memory features could supersede it.

calendar_today 2025-12-30
claude-code anthropic ensue-memory semantic-search context-management
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