Serper

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

Serper AI

I built a real-time YouTube fact-checker with Claude Code

https://reddit.com/link/1ub7w8v/video/3yyn91ou8i8h1/player First shout-out to u/Debate_Witty and InTruth — I've been independently working on this same problem since last September, with my own launch planned for the end of this week. Seeing the response to their post was genuinely encouraging: it confirms there's real demand here. Glad to be coming at it from a different angle. What I built: a Chrome extension that puts real-time fact-check bubbles over YouTube videos as people speak. It pulls real sources from the web, evaluates the claim against them, and shows the verdict — with the sources — right on screen. How Claude Code helped: Claude Code has been my development environment from day one back in September — first in the terminal, and later through the Claude Code extension in VS Code as I moved over to it. I pair-programmed the entire backend with it: the RAG orchestration, the source-waterfall, the caching layer, the verdict-classification taxonomy, and months of iterative QA. Day-to-day debugging, refactors, and deploys all ran through Claude Code. A solo build of this scope simply wasn't realistic without it. Try it free: there's a real free tier — just install and hit play. Plus is $9.99/mo when you want more. Chrome Web Store: search "PopUp Fact Check for YouTube" Landing page: PopUpFactCheck.com 70-min demo: https://www.youtube.com/watch?v=zkprFltMbXM What makes it different: 🔑 No API keys to bring — no OpenAI/Claude/search keys to sign up for, no config. Just install and play. 🧠 Not just True/False — it reads context, flags misleading framing, and calls out rhetoric and opinion dressed up as fact. 👍👎 Vote any bubble up or down — every fact-check (anonymized) feeds back into the QA pipeline, so it improves the more it's used. Under the hood — for the builders: Developed with Claude Code; verdicts generated by GPT-5.4. RAG, grounded in real retrieved sources — never the model's memory. A source waterfall reaches for the most authoritative first: government data (BLS, FRED, IMF), fact-checkers, and news APIs — then web search (DDGS + Serper). A cache sits in front of everything, so repeated claims across videos and viewers are answered instantly, keeping overhead low. Cost-engineered from the input up. The text the model reads is the video's own transcript/captions — not voice-to-text — so there's no speech-recognition bill on every minute watched. Combined with the cache, that's how the backend stays cheap enough for a $9.99 product to be sustainable. The trade-off, by design: a video needs closed captions available, with CC turned on, for fact-checking to run. A continuous-improvement loop — anonymized results + your votes flow into ongoing QA, on top of months tuning the verdict taxonomy, temporal/misleading detection, source quality, and coherence. To use it: turn on the video's closed captions (CC) and play. For regular videos it reads the full transcript; for live streams it uses the live captions if the feed provides them — and after a live broadcast ends, the full transcript usually takes about an hour to become available. Claims then get checked, with context, as they're spoken. I'd genuinely love your feedback — positive, negative, and especially where it falls short. submitted by /u/userpostingcontent [link] [comments]

Built a news tool with Claude I've wanted for a long time

I've always hated when news stories just die and I never hear about them again. I built a site that searches for updates weekly starting from a particular article. It uses a combination of the Serper Google API, Haiku for small judgements, and Sonnet for larger synthesis. It costs about $0.05 for a weekly scan, so that's not bad. The basic way it works is to take the original article and use Haiku to extract search terms and phrases to keep up to date with the story. Not quite, but something like "whatever happened to that story about X". Then, it tries every week to make an update or just say nothing if it can't find anything. Check it out at www.signaltracker.news I've already added tags and some other small things. I'd be interested in feedback, especially if you can think of a better way of doing it. submitted by /u/Nearby-Nebula4104 [link] [comments]

built a factchecker that catches politicians lying in real time

hi everyone ! built this as part of a larger NLP / deception research project at my university, wanted to share in case anyone finds it useful! essentially, it uses transcribed text + linguistic parameters to detect and evaluate checkworthy claims! live text transcribed --> serper finds sources using pure text --> those results sent back into claude for verdicts based on retrieved sources rather than the model’s training data let me know what would make this something you'd use! InTruth - Chrome Web Store submitted by /u/Debate_Witty [link] [comments]

I took Andrej Karpathy's LLM Council concept to the next level (Docker, MCP, Skill, Search, local/cloud model support and much more)

https://preview.redd.it/x7t8zn66si6h1.png?width=3316&format=png&auto=webp&s=f724452561a90e36ac37d86002a291f508928300 I took Andrej Karpathy's LLM Council concept to the next level (Docker, MCP, and local model support) We want better answers from our LLMs, but relying on a single model falls short. So I built The AI Counsel to run two distinct deliberation modes: First, the LLM Council mode. It runs a 3-stage pipeline: individual replies, anonymous peer reviews, and chairman synthesis. This works best for factual questions and direct answers. Second, the LLM Advisors mode. Multiple customizable personas (like The Skeptic, The Strategist, The Ethicist) debate your question across configurable rounds, reaching consensus to deliver a structured verdict. This works best for decisions, strategy, and tradeoffs. I packaged the tool as a Docker container with a built-in MCP server for full API access. You can connect it to any agent that supports MCP, like Hermes or OpenClaw. It comes with a dedicated skill so your agents can call it directly. You can spin it up using local Ollama models or connect free models from OpenCode Zen/Go and NVIDIA NIM. I also built in direct connections to OpenAI, Anthropic, OpenCode, Mistral, and DeepSeek. To ground responses in the latest web information, I added a search engine. It supports DuckDuckGo (free, no API key), Serper, Brave, and TinyFish (all with free tiers). I also integrated Jina AI to fetch full articles for the LLMs to read. EVERYTHING in the tool is configurable, from system prompts to model temperatures. There are advanced debate models for the council. This tool is massive. Free and Fully Open Source. Check it out Repo: https://github.com/jacob-bd/the-ai-counsel submitted by /u/KobyStam [link] [comments]

I spent $0.03 to build a content workflow I thought would cost me hundreds

I'm not a copywriter. Not a marketer. I handle admin stuff at my company and a few days ago I got asked to start prepping social media content. No budget to hire someone, zero experience doing this kind of thing. Claude Code is where most of the real work happens at my job, so I figured there had to be a way to make it work here too. A friend told me to try out Lava, specifically their gateway. Had no clue how it worked tbh, but I connected the Lava MCP to Claude Code and just went for it. Here's what caught me off guard: the moment I connected, I had access to research tools I never signed up for. Exa, Serper, Tavily. No accounts. No API keys. No monthly subscriptions. They were just there through the gateway. My workflow was pretty simple. I had Claude search for trending topics in our industry, give me a take on what actually mattered, and put together a first draft. The output wasn't perfect but it was like 80% there. I looked it over, added some context, tweaked the angle, and had something real to post. Total cost: $0.03. I wanna be clear, I'm not selling anything here. I'm sharing something that happened and worked. For someone in my position (not an expert, no budget, wearing way too many hats), this was kind of a big deal. Not because the content was incredible, but because I could actually do it myself instead of waiting on someone else or spending money we don't have. The thing people miss about automating small workflows like this: it's not just about saving time. It's that it frees you up to focus on stuff that actually needs your brain. Content prep was gonna eat hours every week. Now it doesn't. If you're using Claude Code and haven't tried connecting external tools through an MCP gateway, seriously, give it a shot. The pay-per-use model through Lava meant I didn't have to commit to anything. $0.03 to test whether a workflow works is a pretty solid deal. submitted by /u/Key_Farmer9710 [link] [comments]

Claude Code AWS Gateway

I built an open-source gateway specific for running Claude Code on AWS. Currently when Claude code on Bedrock has limitations such as no web search, and rudimentary observability and user spend/attribution - atleast without deploying or building your own extensions. LiteLLM proxy is most similar to this, but for a lot of companies who only need it for CC, it's overkill. So I built CCAG (Claude Code AWS Gateway). It sits between Claude Code and Bedrock, presents itself as the Anthropic Messages API, and Claude Code enables its full feature set. Inference still runs through your AWS account. What you get out of the box: Web search (DuckDuckGo/Tavily/Serper/custom per user) Virtual API keys so your devs don't need AWS credentials Per-user and per-team budgets (notify, throttle, or hard block) Multi-account/region routing with failover and sticky user routing for cache affinity OIDC SSO (Okta, Azure AD, Google, whatever has a .well-known endpoint) Admin portal with spend analytics, model mix, latency percentiles, tool usage tracking One-command dev onboarding from a Connect page in the portal Webhook, SNS, EventBridge for budget alerts Written in Rust (axum), adds about 1-5ms overhead. Deploy with Docker Compose or AWS CDK (Fargate + RDS) Free, MIT licensed, every feature included. No enterprise tier or feature gates. Still early days - published yesterday, very much a passion project. Next up is custom guardrails (input/output validation rules) and SMTP for budget notifications so you don't need SNS. Would love feedback, feature requests, or just to hear if others are hitting the same Bedrock limitations. GitHub: https://github.com/antkawam/claude-code-aws-gateway Docs: https://antkawam.github.io/claude-code-aws-gateway submitted by /u/antimoto [link] [comments]