Introducing the LorisTools API. Built for teams that need clean crypto...

Uploaded: 2026-06-16T18:58:33.000Z
Duration: PT22.546S
Channel: Loris Tools

0:21

.01.xyz is now live on Loris Tools • Real-time funding rates from 01 alongside 25+ other venues • Open interest and volume tracking to spot positioning shifts as they happen • Liquidation data streaming live for 01's perpetual futures markets • Full historical funding charts: backtest any 01 pair's funding against every other exchange Check it out →

Loris Tools

15,298 views • 5 months ago

0:28

We're making comprehensive, real-time crypto market data accessible to AI agents 🤖 CoinGecko API now supports x402, the open payment protocol developed by Coinbase 🛡️ that lets AI agents (such as OpenClaw🦞 🦞) pay for crypto price and market data using USDC. Learn how it works 👇

CoinGecko

145,274 views • 7 months ago

0:35

The Bloomberg Terminal of Prediction Markets. Private beta is live with Polymarket and Kalshi, delivering actionable insights for serious traders. - Real-time price tracking - Trading volume & liquidity data - Cross-market arbitrage - Recent trades & top holders - Edge discovery across markets - Graded Buy & Sell Signals Built by seasoned data and analytics veterans, to turn data into a trading advantage, now it’s your turn to test it. Private Beta is live. Like and reply for access.

Predictefy

63,461 views • 9 months ago

1:06

OptimAI Search is now on Agentic(.)Market - and we’re bringing the stack to Base. Builders can plug into live, citation-backed context across web, social, and crypto data through MCP, API, and SDK - then pay seamlessly with x402. No brittle workflows. No manual stitching. Just agent-native access to real-time intelligence at scale. And with custom domain agents on the marketplace, specialized knowledge becomes reusable. Search is becoming infrastructure. Build with it: 💡 💡

OptimAI Network

65,249 views • 3 months ago

0:54

I am using Jev to automate technical analysis to get an edge in crypto and stock markets, this is how: - An autoregressive model trained on 12B data points to forecasts price movements - Jev makes decisions over a feature space that includes time-series data, price forecasts, technical indicators, and news feeds This helps you find the best trading opportunities on Hyperliquid as market conditions change in real time Try it out here: As me below for an API key to access the API and MCP server 👇

Brendan Playford

125,477 views • 5 days ago

2:27

BIG UPDATE: Sundae Float 🍨 We're continuing to make Float the best DeFi intelligence platform, with speed, data, and UI/UX improvements across the board. - Faster, richer Pools table - 1H, 1D, 7D & 30D views - Sortable market tables - Better ticker and token search - More filters across every market - Better support for favorited tokens - Market-wide stats at a glance - Faster Exchanges tab - Real-time trades across all markets - Faster global search - USD chart history back to 2022 - Hourly ADA/USD price history - Historical liquidity flows - Accurate CLMM & stableswap pricing across more venues - Counts for active, liquid markets - Clear badges for curve markets - launchpad markets - CSWAP market support - Danogo market support - Danogo Lending data (UI coming soon!) Available now on

Sundae Labs 🍨

12,752 views • 13 days ago

1:21

Today, we’re releasing Polymarket Journalism Tools, a free suite of tools for writers and researchers using prediction market data. Inside: Draft Analyzer: Paste your article and instantly find relevant polymarkets, ranked by volume and salience. Market Timeline: Find which news stories moved the odds, plotted directly on the price history. Suggest a Polymarket: Don't see the market you need? Send your idea directly to our markets creation team. PolyVideo: Sync Polymarket odds with any YouTube video and find the exact moments that the odds moved. API Explorer: Build your own Polymarket data pipelines the easy way. Read More 👇

The Oracle

43,236 views • 5 months ago

0:56

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.

Hive Intelligence

80,968 views • 11 months ago

0:25

8 GITHUB REPOS FOR BUILDING AN AI TRADING STACK Want to understand how autonomous trading systems are actually built? Start here. Not “AI predicts the next candle” bullshit. 8 repos covering agents, backtesting, exchange APIs, market making, RL and execution. 1. AI Hedge Fund Multi-agent setup where different agents analyze a trade from different angles before reaching a conclusion. 2. Freqtrade One of the biggest open-source crypto trading bots. Strategies, backtesting and automated execution. 3. CCXT The infrastructure layer for connecting to Binance, Bybit, OKX and dozens of other exchanges through one API. 4. NautilusTrader Trading infrastructure for research, backtesting and live execution. 5. Hummingbot Market making, arbitrage and liquidity automation. 6. Eliza Framework for autonomous agents that can interact with crypto wallets and onchain systems. 7. FinRL Reinforcement learning for financial trading research. 8. Jesse Python framework for developing and backtesting crypto trading strategies. The stack basically looks like: data → strategy → backtest → risk → execution → agent I’d treat these as a research starting point, not a money printer. Build locally. Test without real funds. Understand the system before giving an agent access to your wallet.

TeddyCEO

143,730 views • 3 days ago

0:24

Strategy backtesting is live on OpenMarket. Free, for everyone. Most backtesters simulate a market that doesn't exist: no funding, no liquidations, fills at exactly the price you hoped for. Ours simulates the market you actually trade. Trade perps? Declare instrument="perps" and the engine runs real isolated-margin math: it tracks your liquidation price from your leverage and maintenance margin, and if a bar gaps through the level, you're filled at the worse price. Like live. Funding isn't a checkbox. funding="data" settles the recorded funding rates from your venue against your position, so the liquidation line creeps closer while you hold, and your funding bill shows up as a line item in the results. Fees split maker/taker the way your venue routes them, and slippage can walk the recorded order book level by level, so size costs what size costs. And when a stop and a target land in the same candle, we resolve it with finer recorded data, down to 1m. When we can't, we assume the worst and count the guess. Every run reports its own precision: your backtest tells you when it guessed. A strategy is 15 lines of kScript, templates included, and it runs on any market on your chart: your Hyperliquid setup with real funding data, your Binance perp, your spot pairs.

OpenMarket

10,037 views • 2 months ago

1:38

I just built an AI agent that’s 10x smarter than anything using basic search APIs. Here’s what nobody’s telling you about AI development right now. Most developers are stuck using limited search APIs. They’re missing social media data, forums, live news, and answer engines. Their AI is effectively blind to 90% of the public web. The result: Stale data. Weak responses. And endless engineering overhead just to stitch everything together. What changed everything for me was Bright Data’s Web Discovery platform. Instead of juggling multiple APIs and unreliable sources, I got real-time access to every public data source through one unified API. Google. Bing. Twitter. Reddit. Instagram. TikTok. ChatGPT. Perplexity. Even historical web archives going back years. Here’s why this actually matters in practice: • One API instead of 10+ fragmented integrations • Real-time, constantly refreshed public web data • Coverage across search engines, social platforms, forums, and answer engines • Consistent data structure that just works • Way less time fighting data plumbing, way more time building intelligence I used it to build a real-time pricing monitor that tracks competitor pricing, social sentiment, and trending topics at the same time. Something that would’ve taken weeks of integration work happened in a single afternoon. The real breakthrough isn’t just access. It’s consistency. Reliability. And freedom. If you’re building search agents, RAG pipelines, or any AI-driven product, you’re handicapping yourself without comprehensive web data. Check the link in the comments to try it yourself. They’re offering trial credits, and the documentation is actually solid. This is the difference between AI products that work and AI products that dominate. Check it out here:

Hasan Toor

100,511 views • 7 months ago

0:51

can't believe i'm dropping this now. bloomberg terminal for basis and funding arbitrage a lot of time and effort went into this, and here's what you get: - scanner for arb setups across 35 cexes and perp dexes - realtime parsing of 9300 unique pairs - bid and ask of both legs are accounted for, not just last or mark price - you can see real returns over 24h, 7d, 30d based on historically paid funding (not just converting current funding into APR) - ability to filter pairs by volume and open interest and most importantly for every pair you can open a detailed chart section that includes: - price chart (including bid ask) - historical in/out spread chart (based on real bid ask) paid funding chart - funding change chart (yes, it's always different and not always equal to funding paid) and yes, all of this is completely free link:

cryppi / perpdexlist

77,326 views • 1 month ago

0:23

i got you - prediction markets need a dedicated trading terminal + analytics dashboard to attract more volume and provide greater clarity to traders on their performance. traders need data visualizations which are geared towards tracking prediction oriented metrics like calibration curve + brier score. after spending months talking to prediction market traders on twitter - i built out this prototype (mock data for now since Kalshi doesn't offer auth in their API). over the last few months i've become prediction market pilled - believing in a future where experts in topics can profit from their knowledge and a world where most people can make better decisions for their future based off of prediction market odds. a world where someone can see the odds of a jerome powell interest rate cut and decide whether or not to buy a house. a world where someone can directly see the odds of an election and have better data on whether they should move somewhere accordingly. (i want to work in prediction markets btw)

steve

17,525 views • 10 months ago

0:22

Architect’s traditional perpetuals exchange AX, one of the fastest-growing regulated derivatives exchanges in history, is opening trading to individuals and omnibus brokers. With $3B notional in <6 months in institutional trading, we’re excited to welcome a new investor class. We launched AX in February with the conviction that building the largest global regulated exchange for traditional asset perpetuals starts with addressing the needs of institutions and professional market participants: robust risk controls, institutional-grade infrastructure, responsible leverage, wash-trading and market manipulation prevention, no internal market maker, and a clear tier-1 regulatory framework. Our GTM strategy was a risk we took based on ambition, industry experience, intuition, and discipline. Our team is now ready to win the opportunities that risk has yielded, in expanding our markets internationally and building what’s needed here in US derivatives markets. AX offers individual traders the same benefits that have enabled our institutional customers to grow the exchange this large this quickly: a market-defining UX, infrastructure built by elite industry experts, superior book liquidity, low fees and open incentive programs, high-throughput and full-featured APIs, competitive margin, 24/7 one-on-one support, no auto-liquidation or ADL. Join us for the next stage of AX and Architect.

Brett Harrison

25,993 views • 2 months ago

1:12

Your AI agent is useless once it needs to interact with the real world. Need email sending? Website hosting? Data scraping? That usually means: → API keys → subscriptions → integrations → hours of setup I gave my AI agent access to Zero, and it built + hosted personalized landing pages automatically without me configuring anything. Zero gives AI agents access to 14,000+ real-world services with no API keys or subscriptions. The coolest part? Everything runs on pay-per-use microtransactions, so you only pay for what you use. If you're building agents, this is worth trying. Get $5 free credit at 👉

Toha Khan

86,826 views • 3 months ago

1:27

how you can use openAI codex & gpt 5.5 completely FREE (the full guide) 100% legit. no subscription, zero API cost. up to 1M+ token/day. you need just an openAI account and here's how to set it up in 5mins. openAI has a program that gives eligible developers free API usage every day in exchange for sharing API data that helps improve future models. it's not a one-time credit, your allowance refreshes daily. depending on your usage tier, you can get access to hundreds of thousands, or even millions, of free tokens every single day on supported models. here's how to activate it: 1️⃣open your API dashboard: 2️⃣go to settings → data controls 3️⃣enable data sharing for your organization or project 4️⃣make sure your account has a positive API balance 5️⃣save the settings if your account is eligible, you'll see a message confirming access to complimentary daily usage. before you turn it on, know the tradeoff: • prompts and outputs from shared projects can be used to improve openai's models • don't use it for confidential information, client work, or sensitive data • eligibility depends on your account type and settings for everyone else, it's an incredible deal. use it to: • learn AI development • build side projects • experiment with codex • test agents and automations • prototype ideas without worrying about API costs most developers burn money testing ideas. this lets you experiment at scale while spending little to nothing.

m0h

70,509 views • 3 months ago

2:24

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,182 views • 1 year ago

1:33

Introducing: OpenRouter for everything. One prepaid balance for every API your agents and products need. It’s the billing and metering layer every AI team needed from day one. An OpenRouter for everything. Every model call, search, scrape, or data request - one key, one balance, charged as it happens at the price you set. The markup is yours. Failed calls cost nothing. Full ledger down to the individual user. 286+ providers. 2,404+ endpoints. And now it fuels our consumer product, Locus Founder. No more juggling provider accounts, month-end invoices, or building your own usage billing system. Teams building agentic products can finally treat their API spend like any other line item: priced, capped, and billed through to their users. Comment “LOCUS” for priority early access. Book a call at

cole

75,907 views • 1 month ago

9:28

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 views • 10 months ago

Live Cam

Video Failed to Load

Loris Tools

Anya Rossi• Live Now

0 Comments

Related Videos

We're making comprehensive, real-time crypto market data accessible to AI agents 🤖 CoinGecko API now supports x402, the open payment protocol developed by Coinbase 🛡️ that lets AI agents (such as OpenClaw🦞 🦞) pay for crypto price and market data using USDC. Learn how it works 👇