GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (57%)
• Errors (30%)
• Sign in (14%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Inverness	Website Down	12 days ago
Quito	Sign in	13 days ago
Junín	Errors	13 days ago
Guadalajara	Errors	13 days ago
Paris	Website Down	13 days ago
Quito	Errors	13 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Lynn Cole (@priestessofdada) reported 2 minutes ago

  There was this one project I wanted to start a month ago. Maybe it's been a couple of months actually. The github replacement. Everybody hates github at the moment, and for good reason. But every project I looked at tried to recreate the github experience, rather than thinking through the problem fresh. And it took me a little to get my head around it. Understanding the core function I'm actually talking about, and trying to think it through. It's been bothering me. And I think part of the problem is that I was being saas brained or blockchain brained like everybody else. It hit me this morning. You don't need to build a saas or integrate torrents or build out a blockchain to make collaboration and deployment happen without github. All you have to do is build the missing half of the protocol. Easy. So I'm building it. More soon.

• 
  VTR Ravi Kumar (@vtrrk) reported 3 minutes ago

  Got connector no working well with ChatGPT and Claude recently. Anyone else facing similar issue. “and the actual GitHub call is still being rejected with “GitHub tool has been disabled.”

• 
  Rhys (@RhysSullivan) reported 3 minutes ago

  @aarondfrancis Across the board are you using a mix of loading secrets from 1password and setting them in Executor or one or the other? Then for GitHub, was it the GitHub API / GraphQL / MCP server? If it's an MCP you OAuth to then it'd be unrelated to 1password so narrowing it from there

• 
  Richard de los Santos (@ZeusRadls) reported 5 minutes ago

  @atmoio Grok Bot is wild. For fun I had it review and fix my LinkedIn page. It asked me some questions and went to the page and made the edits in its local browser. It will now respond to people and pass along useful connections to me. I asked it to push a local Grok Build project to GitHub. It found the project folder fixed some issues and pushed it to GitHub. I asked it clean up my downloads folder. It did it instantly. I asked it to review and clean up my old Gmail account. It went through thousands of old emails. Wiped out my quota doing it, but it was insanely easy. I activated the 𝕏 connector and had it advise me on my 𝕏 activity. It told me to stop positing garbage and clean up my act (basically). I need new tires so I asked Grok Bot to create an agent to monitor prices and let me know when a deal comes up. The list goes on…

• 
  . (@Michigan_X12) reported 6 minutes ago

  @g_inobambino For example even forgetting to close a GitHub project my mistake and that leads to someone stealing your code can get you into more trouble that it should albeit they make it clear in the syllabus to protect your GitHub projects if you use the site.

• 
  Jarkko (@JarSyr) reported 7 minutes ago

  Then SpaceX acquired Cursor on August 14. Three days later, Cursor launched Origin, its own GitHub competitor. And two weeks after that, OpenAI publicly said it wasn’t confident SpaceX would follow its terms and started winding down the relationship. Hard to ignore the timing.

• 
  Mert Hurturk (@merthurturk) reported 8 minutes ago

  Tried @cursor_ai after Claude's limit changes. Connected GitHub, asked the agent to debug issue #276. Cloud env spun up fine... but the agent can't read GitHub issues. PRs, yes. Issues, no. Am I supposed to paste the issue body in manually? What am I missing?

• 
  Matt (@aspim4tt) reported 8 minutes ago

  potato potato potato, GitHub plugin on Grok @bot sees public repos, private ones 404, and re-auth from chat just fails. Please fix it.

• 
  swayam (@swymbnsl) reported 9 minutes ago

  I made my first 1,00,000 INR back in 2023, selling a NFT collection on Canto Blockchain. Locked in for over 5 months, was never into Art but learnt pixel art from here and there and made over 140 different assets. Then generated 5k of those unique NFTs using a broken python script I found on Github. Had zero programming experience back then, and GPT wasn't that good either. Somehow fixed it after a week of trial and error and going through StackOverflow guides. There used to be a very famous Node.js script by Hashlips but it didn't work on my 32bit potato pc. Was ultimately able to sell my artwork, and by the time I swapped the coin, it was worth 1.13L All this for JEE coaching fee cause we weren't able to afford it back then

• 
  Adam (@Adamdesgns) reported 12 minutes ago

  Use Adam’s existing projects when appropriate, including his AI tools, construction applications, research systems, websites, and agent workflows. Create projects that prove skills employers request, such as: Python JavaScript or TypeScript *** and GitHub APIs and JSON SQL and databases Cloud deployment LLM APIs Prompt and context engineering Retrieval-augmented generation Embeddings and vector search Agent workflows Tool calling Testing and evaluation Authentication and permissions Logging and observability AI safety and security Cost and latency management Documentation Product thinking Do not generate an entire project while Adam watches. Build with him. Assign meaningful sections for him to complete, review what he produces, explain mistakes, and require him to understand the final system. Every portfolio project should eventually include: A clear problem statement Intended users Architecture Working code Tests Security considerations Deployment Screenshots or demonstration video README Technical explanation Known limitations Future improvements A short case study A two-minute interview explanation EXPERIENCE LOG Maintain an honest Proof of Work record containing: Project Date Problem solved Adam’s personal contribution Technologies used Technical decisions Bugs diagnosed Skills demonstrated Result Supporting link or file Resume bullet STAR interview story Never claim Adam completed work he did not complete. Never describe AI-generated work as Adam’s independent technical achievement unless he understands, reviewed, modified, and can defend it. JOB-READINESS GATES Do not label Adam job-ready because he finished a course. He is job-ready only when he can: Build a relevant project from a blank starting point. Explain the architecture without reading a script. Debug common failures. Use *** properly. Read documentation. Work with APIs and data. Deploy and monitor an application. Explain security, privacy, cost, and failure risks. Complete realistic technical assignments. Answer role-specific interview questions. Show multiple credible projects. Translate his trade and business experience into relevant professional strengths. ASSESSMENTS Use four types of assessment: Quick recall quizzes Explain-it-back questions Hands-on exercises Closed-book practical challenges Maintain a skills matrix: Not introduced Learning Assisted Independent Job-ready Do not promote a skill to “independent” because Adam completed one guided exercise. JOB SEARCH PREPARATION When Adam approaches job readiness: Research current openings. Extract recurring requirements. Compare them against his skills matrix. Identify the remaining gaps. Build an honest technical resume. Improve his LinkedIn and GitHub presentation. Create role-specific portfolio selections. Practice recruiter screens. Run technical mock interviews. Run behavioral interviews. Develop clear STAR stories. Create targeted applications. Track applications and outcomes. Use rejection feedback to update training. Never submit an application, send a message, register for an exam, purchase a course, or spend money without Adam’s explicit approval. ACADEMIC INTEGRITY You may teach, quiz, explain, review, and prepare Adam. You must not impersonate him, complete a certification exam for him, provide stolen exam questions, or help him cheat on a graded assessment. The goal is for Adam to genuinely possess the skill. OPERATING FILES Create and maintain: Career Target Skills Matrix Certification Roadmap Course Queue Weekly Learning Plan Project Lab Proof of Work Log Portfolio Checklist Interview Question Bank Job Application Tracker Weekly Progress Report Keep records concise, current, and useful. Do not bury Adam under administrative paperwork. PERSONALITY You are demanding, patient, practical, encouraging, and occasionally funny. You are proud when Adam earns progress, but you do not hand out fake praise. You expect him to think, attempt the work, and improve.

• 
  Phil 🪏 (@phil_uplc) reported 15 minutes ago

  Vibe-coders / junior developers, please stop installing AI Plugins and skills from GitHub or third party plugin stores without reading all the skills. Do not trust the number of GitHub stars, forks, issues, commits or PRs, all of these can be, and are, actively gamed. Blackhats buy stars, forks, issues, etc, on forums, these are provided by accounts stolen in phishing campaigns, and often indistinguishable from real users. A huge chunk of the recent jump in credential theft is from this. Blackhat uploads AI skills / deslop / plugins / INSERT_MAGIC_PROMISE_HERE repo, with lots of flashy charts and graphics and a compelling Readme, and a massive AI codebase that users cant bother to read that is an AI slop version of their claim, and put malware, malware installation or credential theft prompts somewhere deep in those thousands of lines of code. I have heard direct accounts from dozens of developers this month who have been cooked by this, or the “coding interview problem” equivalent. Read everything before installation yourself, DO NOT ask AI to audit or read it for you unless you are completely certain of your sandbox or do it in a throwaway remote VM. Prompt injection is alive, and I’ve seen this stuff install malware that escapes most default security measures.

• 
  AI Panda (@AIPandaX) reported 16 minutes ago

  Every AI coding agent already reads your codebase. What if it could understand every dependency before making changes? Inside every codebase is a structure: functions call other functions, files import other files, changes ripple through the system. That structure is not hidden. It is just relationships that any graph can map and any agent can query. There is an open-source tool that turns codebases into knowledge graphs that AI agents can query. It runs entirely in your browser. It is called GitNexus. It started in August 2025 when developers built a client-side knowledge graph creator that indexes repositories without sending code to servers. Drop in a GitHub, GitLab, Azure DevOps repo or ZIP file. Get an interactive knowledge graph with a built-in Graph RAG agent. Works with 21 programming languages. Here is what happens when you use GitNexus. You run npx gitnexus analyze in your repository. It indexes every file, function, class, and dependency. It builds a knowledge graph that tracks every relationship. Connect your coding agent with npx gitnexus setup. Now your agent can query the graph through MCP tools. The problem it solves: AI agents edit code without knowing what depends on it. Agent changes UserService validate function. Doesn't know 47 functions depend on its return type. Breaking changes ship. GitNexus precomputes structure at index time. Clustering. Tracing. Scoring. When your agent asks what depends on UserService, it gets a complete answer in one query. Eight callers. Three clusters. All with confidence scores. No multi-step exploration needed. A team measured impact on code reliability. AI agent without GitNexus: 3 breaking changes per 10 edits because it missed downstream dependencies. Same agent with GitNexus MCP integration: zero breaking changes because it checked impact before editing. Two ways to use it. CLI plus MCP for daily development. Index repos locally. Connect Cursor, Claude Code, Codex, Antigravity, or Windsurf through MCP. Query the graph from your editor. Check impact before changes. Full repos, any size. Web UI for quick exploration. No install needed. Upload a repository or paste a GitHub URL. Explore the graph visually. Chat with the built-in Graph RAG agent. Runs entirely in browser with LadybugDB WASM. The graph shows more than connections. Community clustering groups related code. Execution flow traces how data moves. Call chains map function dependencies. Risk scores identify fragile areas. All computed at index time, not query time. MCP tools for agents. Impact analysis shows what breaks when you change a function. Dependency trace reveals who calls your code. Architecture view maps domains and boundaries. Execution flow follows data through the system. Change risk scores affected files. Works with 21 languages. TypeScript, JavaScript, Python, Go, Rust, Java, C, C++, C#, PHP, Ruby, Swift, Kotlin, Dart, Vue, HTML, CSS, Shell, PowerShell, Dockerfile, Jinja. Tree-sitter parsing with native and WASM backends. LadybugDB for graph storage. Native version for CLI with persistence. WASM version for browser with in-memory storage. Bridge mode connects them: web UI can browse CLI-indexed repos. One command setup. Analyze creates the graph, installs agent skills, registers hooks, and writes context files. Setup configures MCP so agents can query the graph. Works with Claude Code, Cursor, Codex, and other MCP-compatible editors. Optional embedding support for semantic search. Deploy to Render with one click for team access. Self-hosted backend mode for unlimited scale. Access control with token authentication. 46.3k+ stars on GitHub. Created August 2025. Active development with new language support and agent integrations. Every codebase already has structure. GitNexus maps it so agents can see before they change.

• 
  Loftwah (@loftwah) reported 17 minutes ago

  @fjzeit How much of the code though? I've had some where I have to look at the code but not very deeply. More like skim over the code. My process is actually to grill the agent about everything I don't like and create GitHub issues for all of it with the intended solution inline.

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 18 minutes ago

  CC SWITCH JUST FIXED THE WORST PART OF USING AI CODING TOOLS. And the biggest feature isn’t switching models. It’s what happens when your entire setup starts working like one system. What CC Switch replaces: → Manually editing JSON, TOML, and ENV files just to change providers → Rebuilding the same MCP server setup across Claude Code, Codex, Gemini CLI, OpenCode, and Hermes → Re-entering keys, endpoints, prompts, and configs every time you change tools What you get instead: ✓ One desktop app managing 7 AI tools ✓ 50+ ready-made provider presets including AWS Bedrock and NVIDIA NIM ✓ One-click provider switching directly from your system tray ✓ Unified MCP management with two-way syncing ✓ One-click skill installs from GitHub repos or ZIP files The underrated part: → Local proxy + auto-failover can switch to a backup provider when your main one dies → Universal providers let one config sync across Claude Code, Codex, and Gemini CLI → Prompts can be written once in Markdown and synced across tool files → Usage tracking, session restoration, cloud sync, and automatic backups are built in too CC Switch is free, open source, and runs on Windows, Mac, and Linux. The AI model wasn’t always the bottleneck. Your setup was.

• 
  Brij Pandey (@LearnWithBrij) reported 19 minutes ago

  Everyone is shipping MCP servers. Far fewer people can explain what MCP actually is. Here is the whole protocol on one page. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 Four models and five tools used to mean twenty custom integrations. MCP turns N x M into N + M. One protocol, any model, any tool. 𝗧𝗵𝗲 𝗺𝗲𝗻𝘁𝗮𝗹 𝗺𝗼𝗱𝗲𝗹 Host is the AI app: Claude Desktop, Cursor, Claude Code. Client lives inside the host, one per connected server. Server exposes capabilities. Host contains Client. Client talks to Server. All of it rides on JSON RPC 2.0. 𝗧𝗵𝗿𝗲𝗲 𝗽𝗿𝗶𝗺𝗶𝘁𝗶𝘃𝗲𝘀, 𝘁𝗵𝗿𝗲𝗲 𝗼𝘄𝗻𝗲𝗿𝘀 Tools: model controlled. The AI decides when to call. Resources: app controlled. The app injects context. Prompts: user controlled. The user explicitly invokes. Most confusion about MCP comes from collapsing these three into one bucket. 𝗧𝘄𝗼 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁𝘀 stdio for local subprocesses like filesystem and ***. Streamable HTTP for remote services like GitHub and Notion. It replaced legacy SSE in 2025. 𝗪𝗵𝗮𝘁 𝗻𝗼𝗯𝗼𝗱𝘆 𝘁𝗲𝗹𝗹𝘀 𝘆𝗼𝘂 Token tax: 50 tools at 50 tokens each is 2,500 schema tokens burned per turn. OAuth sprawl: secret rotation across many servers is a real ops cost. Tool sprawl: more servers, more failure surface. Schema drift: a server changes and your agent quietly breaks. Observability gap: tracing across the boundary is still hard. 𝗧𝗵𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆 MCP is not magic. It is plumbing. Simple primitives, clean transport, open standard. That is exactly why it became the default in eighteen months. Build tools. Expose via MCP. Ship value. Repeat. Where does the line sit for you: at what point does a protocol stop being an integration convention and start being infrastructure that platform teams have to govern like a network layer?

• 
  Toufiq Qureshi (@Toufiq651) reported 20 minutes ago

  Day 2 of building an AI interviewer 🧠 Yesterday I said the AI interviews you on your own code. Today, the thing that actually makes that work. Here's what happens if you just hand an LLM a job title and ask for interview questions: "What is React?" "Explain the difference between let and var." "What are microservices?" Useless. Anyone can Google that. It's the same interview for every candidate. The problem isn't the model. It's that the model has no idea what you built. So the AI interviewer runs an analysis phase BEFORE the interview ever starts: 1. You log in with GitHub OAuth 2. You pick your most complex repo 3. Backend downloads it, scores every file, extracts the architecturally significant parts 4. The AI reads that context and generates questions from it Now the same model asks: "Why did you use a Singleton here when it breaks under concurrent access?" Same LLM. Same temperature. Completely different interview. One more design decision that matters more than it looks: Analysis and interview are separate phases. Analysis is the expensive part — repo download, extraction, a big LLM call. So it runs once and gets cached in Postgres. Every interview after that on the same repo is nearly free. The lesson I keep relearning: when AI output feels generic, the fix is almost never a cleverer prompt. It's better context.

• 
  Jarno (@onefinalprompt) reported 23 minutes ago

  GitHub stars: the only currency where getting rich just means more people expect you to fix their bugs for free.

• 
  Mohd Zaid (@BuildWithZaid) reported 25 minutes ago

  This is Claude running an MCP server connected to Notion, GitHub, and Slack simultaneously. No switching tabs. No copying data between tools. One conversation handles everything. Claude reads the GitHub issue, checks the Notion project brief, and sends a Slack update...

• 
  kethic (@kethcode) reported 25 minutes ago

  so... @github automation flagging appeals... can anyone help? lost visibility to the last 20 issues and apparently we need to appeal some sort of invisibility flag for our issue curation account?

• 
  chaos (@konig0000) reported 33 minutes ago

  Two years ago, I got rejected in the final round of a top product company. I had built 5 flashy fullstack projects on GitHub and thought I was invincible. In the interview: • DSA Round: I couldn't write the $O(N)$ sliding window solution under pressure. • System Design Round: I couldn't explain how to shard a PostgreSQL database without downtime. I stopped building tutorial side-projects for 6 months: - 100 Medium DSA pattern problems. - 15 classic System Design architectures

• 
  KSK Lab (@ksk_tinylab) reported 37 minutes ago

  My Codex philosophy: I start local, keep things simple, and understand what runs before giving it more access. If I wouldn’t install it at work just because it looks useful, I won’t blindly trust it at home. GitHub stars ≠ security review. Slow is fine. Cleanup isn’t.

• 
  AiMind (@AIMind_Ai) reported 39 minutes ago

  3 websites replace 20 hours of googling when you build a home server. The hard part of self-hosting is not the hardware. A used HP EliteDesk and a wall-mounted NAS cost almost nothing. The hard part is not knowing what you can even run, or how to avoid breaking the system on the first command. The first keeps a catalogue of self-hosted alternatives. Look up a replacement for Google Photos, Dropbox, or Notion, and you see what already exists, how many GitHub stars it has, and whether it is still alive. Plus a weekly digest of what shipped. The second lets you run any Linux distro straight in the browser. Arch, Debian, Alpine, Bazzite. Click once, and you are inside a live system, with no evening lost to a USB stick and a real install. The third handles the worst part. Install scripts for Proxmox: Immich, Jellyfin, Vaultwarden, AdGuard, Nginx Proxy Manager. Paste one line into the console and the container comes up on its own. Immich shows 17,735 installs; Docker 36,408. Each of those services used to cost an evening of documentation and three Stack Overflow tabs. Now it is one command. The hardware takes an hour to buy. These 3 bookmarks save you a month. Names in the replies.

• 
  Luka (@dxman1a) reported 44 minutes ago

  @todaywasawesome Top two are correct. Android is not Linux in the traditional sense (yes quite literally the yserlabd is wildly different and is separate from the kernel), 4th is correct, GitHub is NOT A WRAPPER, it's a server. If you're doing to do this to promote slop omarchy get facts right.

• 
  Artem (@xoleeep) reported 46 minutes ago

  this might be the most efficient way to turn a github issue into content 💀

• 
  MemoLabs (@MemoLabsOrg) reported 50 minutes ago

  Earlier, the largest-ever credential leak occurred: 16 billion login credentials—usernames and passwords for Google, Apple, Facebook, and GitHub accounts—were bundled and posted online. This means that the “digital identities” of billions of people, which had long been stored in a centralized database, were stolen all at once. Identity should not exist in this way. DataDID puts identity back in the hands of the individual: self-sovereign ownership, self-authorization, and control over one’s own private keys.

• 
  Phil Hie (@philhie) reported 51 minutes ago

  @github hide closed sub-issues alone will clean up half my boards lol

• 
  Ofer Shapira (@ofer_shapira) reported 52 minutes ago

  Connected to our repo through GitHub CLI, it ran the searches, matched the error spike to recent changes, and found the smoking gun in seconds.

• 
  TullariS (@Tullari5) reported 52 minutes ago

  @capsraunak ok there aren't any errors. please commit, push and share the GitHub URL.

• 
  The Boring Developer (@boringdev77) reported 52 minutes ago

  @torronen @thsottiaux the exponential growth makes sense in hindsight... bigger main thread means bigger copies means bigger cleanup debt. months of that compounds fast. glad the github issue exists, at least it's a known pattern now and not just your setup

• 
  OKECHUKWU_🧑‍💻 (@Okechuqu) reported 57 minutes ago

  If your GitHub is full of clean, finished tutorial clones, you’re actually falling behind the dev who’s been stuck on one ugly, broken project for three weeks.