Nirmal V@lamrin

eMCP marketplace enables developers to deploy, discover, and monetize Model Context Protocol (MCP) tools using the x402 payment standard integrated with Coinbase's Web3 infrastructure. The platform bridges the gap between AI tool creators and users through microtransactions. Core Features: - Cloud-Hosted MCPs: All MCP servers are deployed to cloud infrastructure (Render.com) ensuring 24/7 availability and reliability for tool consumers - x402 Payment Protocol: Seamless pay-per-use tool calls via crypto wallets using the x402 standard, enabling micropayments for individual MCP tool interactions - Automated Deployment: GitHub-to-cloud deployment pipeline with real-time status monitoring and automatic service provisioning - Tool Discovery: Automatic parsing of live MCP servers to extract available tools with embedded pricing (COST: $X.XX format) - Dynamic Pricing: Developers embed costs directly in tool descriptions, automatically parsed to enable monetized interactions without additional configuration Technical Implementation: Built on Supabase for persistence and Render API for cloud hosting. The x402 transport layer intercepts MCP tool calls, processing crypto payments before execution using viem and Base Sepolia. Creators simply annotate tool descriptions with pricing, and the platform handles payment collection and service orchestration, enabling effortless monetization of specialized AI tools and agents in the expanding MCP ecosystem.

Podcasts are an excellent source of knowledge. But they can be too long and hard to pay attention to it the entire time. What if there is a more intuitive way to search for podcasts and also for info within podcasts? This is where our product comes into play. Key highlights 1. Searching for podcasts suited to your taste 2. Searching for answers within a podcast itself by asking it queries and without listening 3. Marking exactly where the answer is and summarising it. 4. Telling user what queries this podcast answers Major Uplifts: 1. Generating queries for dialogues in transcript using the prompt - "Generate 5 questions for the following passage {passage}" 2. Training a classifier using cohere api using the generated queries and dialogues 3. Highly scalable architecture 4. Podcast is just an example. Most documentation (python libraries, eth doc) have only keyword search. It is possible to scrape the documentation and build an index for a search engine using our architecture easily.

🗓️ This will be a 7-day virtual hackathon from 13-20 January 💻 Access AI21 Labs' state-of-the-art language models to build innovative applications 🏆 Prizes and awards of up to $9000 API credits + $3500 cash 💡 Meet and learn from AI21 Labs and Lablab experts 👥 Join the community and find your team ✔️ All levels are welcome 📖 AI tutorials and mentors to help you ⭐ Receive a certificate of completion and Wordtune premium for submission 🐱‍💻 Sign up now! It’s free!

🗓️ This will be a 48-Hour Virtual Hackathon from 2 - 4 December 💻 Technology: You will build applications with generative AI supplied by Cohere ✔️ Level: All levels are welcome 😊 For whom?: Builders, creators & innovators! 💲 The Event is totally free! 🏆 $2000 cash prize pool!

🗓️ This will be a 7-day virtual hackathon from 16-23 December 💻 Build AI application with the latest large language model-powered technology by Cohere 💡 Get the chance to work with the best AI professionals in the industry and learn from them ✔️Entry level = 0. You’ve just started with AI? Are you an experienced Data Scientist? Or maybe you are a Designer or Business Developer? Join us! We need your domain knowledge! 🐱‍💻 Register now and let's get started! It’s free!