Crypto Basics

What are NFTs? NFT Art Explained | Future of NFTs

Learn more about NFTs and their future.
Token Metrics Team
6 minutes
MIN

You may have heard of CryptoPunks, Bored Ape Yacht Club, and VeeFriends, but you may not understand what they are. These names may sound like random combinations of words, but they actually represent some of the most valuable non-fungible token (NFT) projects that have emerged in the past few years.

The world of crypto art and NFTs may appear complex and mysterious, with a mix of celebrities, influencers, and internet experts. But it's not as confusing as it seems. Let's start from the beginning.

What Is An NFT?

Nearly all crypto art that has been introduced to the market has been done so through the minting of non-fungible tokens (NFTs). NFTs are digital assets that have verified proof of ownership. While "fungible tokens" like the US dollar can be easily traded (like exchanging 4 quarters for a dollar), each NFT is unique and cannot be easily traded. For example, imagine a sketch of "Starry Night" by Vincent Van Gogh that has been authenticated by a fine art appraiser as an original. This sketch would be non-fungible because you could not easily exchange it for, say, an original sketch by Leonardo da Vinci. This concept is easy to understand with tangible items like art pieces or collectible cards, but when digital assets can range from a celebrity tweet to an iconic meme to a picture of a pimped out animated ape, it may be confusing.

How Can We Ensure Unique Authenticity?

This is where NFTs enter the scene. Say you are a graphic design artist who just finished your newest 1-of-1 piece of work and you want to sell it as an NFT. Whoever purchases this piece would not only receive the artwork but they would also receive a “digital receipt” that proves that this exact piece is original, unique and authentic.

“But What If I Just Screenshot This Digital Artwork? Wouldn’t I Technically Own the Piece as Well?”

This is the first question that many have mockingly asked on social media and internet forums. The easy answer: yes, you can screenshot practically all digital artwork, but no, that does not mean you own it.

For example, millions of people swarm into the Louvre every year, waiting patiently amidst a giddy crowd, just to capture a picture of the priceless Mona Lisa. Obviously, a picture of the Mona Lisa saved on your iPhone camera roll does not mean that you own that painting.

NFTs work the same way.

Just as the Louvre paid millions of dollars to own, maintain, and display the Mona Lisa in their museum, NFT buyers do the same. However, the main difference is that instead of paying dollars to house the art in a fancy museum, they are paying with cryptocurrency and housing their art in a virtual showcase, so to speak.

This is the basis for how NFTs, cryptocurrency, and blockchain technology are establishing a new and lucrative market for digital art and artists.

The Art of Being Digital

In a 2021 interview, Gary Vaynerchuk (founder of Vayner Media and creator of VeeFriends) made the following statement regarding NFTs. The interviewer remarks on the tangibility of NFTs stating, "the digital aspect, like, you can't see it" — Gary jumps in:

"Well, you can't see a blue check on Instagram? I don't walk around the world with a blue check tattooed on my forehead, but everybody sees it. You can't see my 9 million followers on Instagram, or can you? I would argue the reverse. I would argue that people can't see most of the fancy things you have in your house; that people can see more digital than real life."

And he's onto something, and I'd like to call that something "The Art of Being Digital". In our highly digitized world, our online outreach and interconnectivity is wildly amplified. Gary Vee currently has 9.9 million followers on Instagram — but without access to the internet — he has no way of interacting with that community and tapping into the true power of those 9.9 million people.

Why Do NFTs Have Value?

The value of an NFT is determined by the collective intentionality of those who are willing to buy and sell them. In other words, the value of an NFT is based on what people are willing to pay for it. This is similar to the way that the value of traditional art is determined by the market, with the value being based on factors such as the artist's fame and the rarity of the work.

The Tom Brady example illustrates this idea. On the surface, it might seem strange that someone would pay $430k for a digital picture of a cartoon ape. However, if we consider the fact that the buyer was Tom Brady and the seller was the well-known digital artist Trevor Jones, it becomes clearer that the value of the NFT was determined by the collective intentionality of those involved in the transaction.

Furthermore, the digital art of NFTs offers more than just a digital file and a high price tag. NFTs provide the ability for digital artists to monetize their work and for collectors to own and trade unique digital items. This opens up new opportunities for artists and collectors alike, and has led to the growth of a vibrant and exciting market for NFTs.

Join The Club

Celebrities such as Tom Brady, Post Malone, Steph Curry, and Jimmy Fallon have been buying Bored Ape NFTs. Bored Ape NFTs were introduced by the Bored Ape Yacht Club (BAYC) in April 2021 at a price of 0.08 Ethereum (ETH) each, or about $190 at the time. Since then, the price of Bored Apes has increased significantly, yielding substantial returns for early investors.

In addition to the potential for financial gain, buying a Bored Ape NFT also grants the buyer access to the BAYC community. This includes access to the BAYC Discord, where buyers can connect with other members of the club, including celebrities, and collaborate on NFT-related projects. BAYC also gives members priority access to future NFT drops, allowing them to expand their collections.

Minting and selling NFTs can also be highly lucrative for those who create their own NFT projects. This is another reason why celebrities and others may be interested in the NFT market. Creating and selling NFTs allows artists and other creators to monetize their digital work and gives collectors the opportunity to own unique digital items. The growth of the NFT market has created new opportunities for both artists and collectors, leading to a vibrant and exciting market for NFTs.

Blockchain, Smart Contracts, and Secondary Sales

Blockchain technology is used to record the conversion of traditional currency into cryptocurrency, such as Ethereum (ETH), in the NFT market. This transaction is recorded on the blockchain as public information that is easily accessible to anyone who wants to view it. This ensures transparency and helps to prevent fraud in the NFT market.

Smart contracts are programs stored on the blockchain that allow NFT creators to stipulate the conditions of resale. For example, a creator could draft a smart contract that allows them to earn a 10% commission on any subsequent resales of their NFT. This allows creators to continue to benefit from the success of their work, even after the initial sale.

Smart contracts also facilitate secondary sales in the NFT market. When the value of an NFT increases, the smart contract associated with that NFT can automatically distribute any profits from the sale to the relevant parties, such as the creator or the NFT platform. For example, if the value of Tom Brady's Bored Ape NFT increased from $430k to $530k, the smart contract could automatically distribute the $100k profit to the Bored Ape Yacht Club, if that was stipulated in the contract.

This use of smart contracts helps to ensure that all parties are fairly compensated for their contributions to the NFT market, and it allows for efficient and transparent transactions without the need for intermediaries.

The Future Of Crypto-Art

Grammy-winning artist Tyler, the Creator recently questioned the value of NFTs, stating that most of the examples he has seen are not "beautiful art." While art is subjective and many NFTs are AI-generated, there are still many ways in which NFTs can offer value in the real world.

First, NFTs can be used to represent tangible experiences and achievements. Instead of framing a concert ticket or a season pass, these items could be represented as NFTs, allowing individuals to proudly display their experiences and achievements in the digital world. This could be especially beneficial for VIP experiences and exclusive memberships.

Second, NFTs can provide a level of authenticity and scarcity that cannot be achieved with physical items. This is especially useful for limited edition items and collectibles, which can be authenticated and traded easily on the blockchain.

Third, the use of smart contracts can ensure that all parties are fairly compensated for their contributions to the NFT market. This allows for transparent and efficient transactions without the need for intermediaries.

Overall, while some may dismiss NFTs as "silly little digital artworks," they have the potential to reshape not just the art world, but the world itself.

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Backtesting Token Metrics AI: Can AI Grades Really Predict Altcoin Breakouts?

Token Metrics Team
5 min
MIN

To test the accuracy of Token Metrics' proprietary AI signals, we conducted a detailed six-month backtest across three different tokens — Fartcoin, Bittensor ($TAO), and Ethereum. Each represents a unique narrative: memecoins, AI infrastructure, and blue-chip Layer 1s. Our goal? To evaluate how well the AI’s bullish and bearish signals timed market trends and price action.

Fartcoin:

The green and red dots on the following Fartcoin price chart represent the bullish and bearish market signals, respectively. Since Nov 26, 2024, Token Metrics AI has given 4 trading signals for Fartcoin. Let’s analyze each signal separately.

The Fartcoin chart above displays green and red dots that mark bullish and bearish signals from the Token Metrics AI, respectively. Over the last six months — starting November 26, 2024 — our system produced four significant trade signals for Fartcoin. Let’s evaluate them one by one.

The first major signal was bullish on November 26, 2024, when Fartcoin was trading at $0.29. This signal preceded a massive run-up, with the price topping out at $2.49. That’s an astounding 758% gain — all captured within just under two months. It’s one of the most powerful validations of the AI model’s ability to anticipate momentum early.

Following that rally, a bearish signal was triggered on January 26, 2025, just before the market corrected. Fartcoin retraced sharply, plunging 74.76% from the highs. Traders who acted on this bearish alert could have avoided substantial drawdowns — or even profited through short-side exposure.

On March 25, 2025, the AI turned bullish again, as Fartcoin traded near $0.53. Over the next several weeks, the token surged to $1.58, a 198% rally. Again, the AI proved its ability to detect upward momentum early.

Most recently, on June 1, 2025, Token Metrics AI flipped bearish once again. The current Trader Grade of 24.34 reinforces this view. For now, the system warns of weakness in the memecoin market — a trend that appears to be playing out in real-time.

Across all four trades, the AI captured both the explosive upside and protected traders from steep corrections — a rare feat in the volatile world of meme tokens.

Bittensor

Next, we examine Bittensor, the native asset of the decentralized AI Layer 1 network. Over the last six months, Token Metrics AI produced five key signals — and the results were a mixed bag but still largely insightful.

In December 2024, the AI turned bearish around $510, which preceded a sharp decline to $314 by February — a 38.4% drawdown. This alert helped traders sidestep a brutal correction during a high-volatility period.

On February 21, 2025, the system flipped bullish, but this trade didn't play out as expected. The price dropped 25.4% after the signal. Interestingly, the AI reversed again with a bearish signal just five days later, showing how fast sentiment and momentum can shift in emerging narratives like AI tokens.

The third signal marked a solid win: Bittensor dropped from $327 to $182.9 following the bearish call — another 44% drop captured in advance.

In April 2025, momentum returned. The AI issued a bullish alert on April 19, with TAO at $281. By the end of May, the token had rallied to over $474, resulting in a 68.6% gain — one of the best performing bullish signals in the dataset.

On June 4, the latest red dot (bearish) appeared. The model anticipates another downward move — time will tell if it materializes, but the track record suggests caution is warranted.

Ethereum

Finally, we analyze the AI’s predictive power for Ethereum, the second-largest crypto by market cap. Over the six-month window, Token Metrics AI made three major calls — and each one captured critical pivots in ETH’s price.

On November 7, 2024, a green dot (bullish) appeared when ETH was priced at $2,880. The price then surged to $4,030 in less than 40 days, marking a 40% gain. For ETH, such a move is substantial and was well-timed.

By December 24, the AI flipped bearish with ETH trading at $3,490. This signal was perhaps the most important, as it came ahead of a major downturn. ETH eventually bottomed out near $1,540 in April 2025, avoiding a 55.8% drawdown for those who acted on the signal.

In May 2025, the AI signaled another bullish trend with ETH around $1,850. Since then, the asset rallied to $2,800, creating a 51% gain.

These three trades — two bullish and one bearish — show the AI’s potential in navigating large-cap assets during both hype cycles and corrections.Backtesting Token Metrics AI across memecoins, AI narratives, and Ethereum shows consistent results: early identification of breakouts, timely exit signals, and minimized risk exposure. While no model is perfect, the six-month history reveals a tool capable of delivering real value — especially when used alongside sound risk management.

Whether you’re a trader looking to time the next big altcoin rally or an investor managing downside in turbulent markets, Token Metrics AI signals — available via the fastest crypto API — offer a powerful edge.

Backtesting Token Metrics AI across memecoins, AI narratives, and Ethereum shows consistent results: early identification of breakouts, timely exit signals, and minimized risk exposure. While no model is perfect, the six-month history reveals a tool capable of delivering real value — especially when used alongside sound risk management.

Whether you’re a trader looking to time the next big altcoin rally or an investor managing downside in turbulent markets, Token Metrics AI signals — available via the fastest crypto API — offer a powerful edge.

Research

Token Metrics API vs. CoinGecko API: Which Crypto API Should You Choose in 2025?

Token Metrics Team
7 min
MIN

As the crypto ecosystem rapidly matures, developers, quant traders, and crypto-native startups are relying more than ever on high-quality APIs to build data-powered applications. Whether you're crafting a trading bot, developing a crypto research platform, or launching a GPT agent for market analysis, choosing the right API is critical.

Two names dominate the space in 2025: CoinGecko and Token Metrics. But while both offer access to market data, they serve fundamentally different purposes. CoinGecko is a trusted source for market-wide token listings and exchange metadata. Token Metrics, on the other hand, delivers AI-powered intelligence for predictive analytics and decision-making.

Let’s break down how they compare—and why the Token Metrics API is the superior choice for advanced, insight-driven builders.

🧠 AI Intelligence: Token Metrics Leads the Pack

At the core of Token Metrics is machine learning and natural language processing. It’s not just a data feed. It’s an AI that interprets the market.

Features exclusive to Token Metrics API:

  • Trader Grade (0–100) – Short-term momentum score based on volume, volatility, and technicals
  • Investor Grade (0–100) – Long-term asset quality score using fundamentals, community metrics, liquidity, and funding
  • Bullish/Bearish AI Signals – Real-time alerts based on over 80 weighted indicators
  • Sector-Based Smart Indices – Curated index sets grouped by theme (AI, DeFi, Gaming, RWA, etc.)
  • Sentiment Scores – Derived from social and news data using NLP
  • LLM-Friendly AI Reports – Structured, API-returned GPT summaries per token
  • Conversational Agent Access – GPT-based assistant that queries the API using natural language

In contrast, CoinGecko is primarily a token and exchange aggregator. It offers static data: price, volume, market cap, supply, etc. It’s incredibly useful for basic info—but it lacks context or predictive modeling.

Winner: Token Metrics — The only crypto API built for AI-native applications and intelligent automation.

🔍 Data Depth & Coverage

While CoinGecko covers more tokens and more exchanges, Token Metrics focuses on providing actionable insights rather than exhaustively listing everything.

Feature                                                   Token Metrics API                                    CoinGecko API

Real-time + historical OHLCV              ✅                                                          ✅

Trader/Investor Grades                        ✅ AI-powered                                     ❌

Exchange Aggregation                         ✅ (Used in indices, not exposed)     ✅

Sentiment & Social Scoring                  ✅ NLP-driven                                     ❌

AI Signals                                               ✅                                                         ❌

Token Fundamentals                            ✅ Summary via deepdive         ⚠️ Limited

                                                                        endpoint

NFT Market Data                                  ❌                                                          ✅

On-Chain Behavior                               ✅ Signals + Indices                   ⚠️ Pro-only (limited)

If you're building something analytics-heavy—especially trading or AI-driven—Token Metrics gives you depth, not just breadth.

Verdict: CoinGecko wins on broad metadata coverage. Token Metrics wins on intelligence and strategic utility.

🛠 Developer Experience

One of the biggest barriers in Web3 is getting devs from “idea” to “prototype” without friction. Token Metrics makes that easy.

Token Metrics API Includes:

  • SDKs for Python, Node.js, and Postman
  • Quick-start guides and GitHub sample projects
  • Integrated usage dashboard to track limits and history
  • Conversational agent to explore data interactively
  • Clear, logical endpoint structure across 21 data types

CoinGecko:

  • Simple REST API
  • JSON responses
  • Minimal docs
  • No SDKs
  • No built-in tooling (must build from scratch)

Winner: Token Metrics — Serious devs save hours with ready-to-go SDKs and utilities.

📊 Monitoring, Quotas & Support

CoinGecko Free Tier:

  • 10–30 requests/min
  • No API key needed
  • Public endpoints
  • No email support
  • Rate limiting enforced via IP

Token Metrics Free Tier:

  • 5,000 requests/month
  • 1 request/min
  • Full access to AI signals, grades, rankings
  • Telegram & email support
  • Upgrade paths to 20K–500K requests/month

While CoinGecko’s no-login access is beginner-friendly, Token Metrics offers far more power per call. With just a few queries, your app can determine which tokens are gaining momentum, which are losing steam, and how portfolios should be adjusted.

Winner: Token Metrics — Better for sustained usage, scaling, and production reliability.

💸 Pricing & Value

Plan Feature                CoinGecko Pro            Token Metrics API

Entry Price                  ~$150/month                $99/month

AI Grades & Signals            ❌                               ✅ 

Sentiment Analytics            ❌                               ✅

Sector Index Insights          ❌                               ✅

NLP Token Summaries       ❌                                ✅

Developer SDKs                  ❌                                ✅

Token-Based Discounts     ❌                                ✅ (up to 35% with $TMAI)

For what you pay, Token Metrics delivers quant models and intelligent signal streams — not just raw price.

Winner: Token Metrics — Cheaper entry, deeper value.

🧠 Use Cases Where Token Metrics API Shines

  • Trading Bots
    Use Trader Grade and Signal endpoints to enter/exit based on AI triggers.
  • GPT Agents
    Generate conversational answers for “What’s the best AI token this week?” using structured summaries.
  • Crypto Dashboards
    Power sortable, filtered token tables by grade, signal, or narrative.
  • Portfolio Rebalancers
    Track real-time signals for tokens held, flag risk zones, and show sector exposure.
  • LLM Plugins
    Build chat-based investment tools with explainability and score-based logic.

🧠 Final Verdict: CoinGecko for Info, Token Metrics for Intelligence

If you're building a crypto price tracker, NFT aggregator, or exchange overview site, CoinGecko is a solid foundation. It’s reliable, broad, and easy to get started.

But if your product needs to think, adapt, or help users make better decisions, then Token Metrics API is in another class entirely.

You're not just accessing data — you're integrating AI, machine learning, and predictive analytics into your app. That’s the difference between showing the market and understanding it.

🔗 Ready to Build Smarter?

  • ✅ 5,000 free API calls/month
  • 🤖 Trader & Investor Grades
  • 📊 Live Bull/Bear signals
  • 🧠 AI-powered summaries and GPT compatibility
  • ⚡ 21 endpoints + Python/JS SDKs

👉 Start with Token Metrics API

Research

Python Quick-Start with Token Metrics: The Ultimate Crypto Price API

Token Metrics Team
10 min
MIN

If you’re a Python developer looking to build smarter crypto apps, bots, or dashboards, you need two things: reliable data and AI-powered insights. The Token Metrics API gives you both. In this tutorial, we’ll show you how to quickly get started using Token Metrics as your Python crypto price API, including how to authenticate, install the SDK, and run your first request in minutes.

Whether you’re pulling live market data, integrating Trader Grades into your trading strategy, or backtesting with OHLCV data, this guide has you covered.

🚀 Quick Setup for Developers in a Hurry

Install the official Token Metrics Python SDK:

pip install tokenmetrics

Or if you prefer working with requests directly, no problem. We’ll show both methods below.

🔑 Step 1: Generate Your API Key

Before anything else, you’ll need a Token Metrics account.

  1. Go to app.tokenmetrics.com/en/api
  2. Log in and navigate to the API Keys Dashboard
  3. Click Generate API Key
  4. Name your key (e.g., “Development”, “Production”)
  5. Copy it immediately — keep it secret.

You can monitor usage, rate limits, and quotas right from the dashboard. Track each key’s status, last used date, and revoke access at any time.

📈 Step 2: Retrieve Crypto Prices in Python

Here’s a simple example to fetch the latest price data for Ethereum (ETH):

import requests

API_KEY = "YOUR_API_KEY"

headers = {"x-api-key": API_KEY}

url = "https://api.tokenmetrics.com/v2/daily-ohlcv?symbol=ETH&startDate=<YYYY-MM-DD>&endDate=<YYYY-MM-DD>"

response = requests.get(url, headers=headers)

data = response.json()

for candle in data['data']:

    print(f"Date: {candle['DATE']} | Close: ${candle['CLOSE']}")

You now have a working python crypto price API pipeline. Customize startDate or endDate to get specific range of historical data.

📊 Add AI-Powered Trader Grades

Token Metrics’ secret sauce is its AI-driven token ratings. Here’s how to access Trader Grades for ETH:

grade_url = "https://api.tokenmetrics.com/v2/trader-grades?symbol=ETH&limit=30d"

grades = requests.get(grade_url, headers=headers).json()['data']

for day in grades:

    print(f"{day['DATE']} — Trader Grade: {day['TA_GRADE']}")

Use this data to automate trading logic (e.g., enter trades when Grade > 85) or overlay on charts.

🔁 Combine Data for Backtesting

Want to test a strategy? Merge OHLCV and Trader Grades for any token:

import pandas as pd

ohlcv_df = pd.DataFrame(data['data'])

grades_df = pd.DataFrame(grades)

combined_df = pd.merge(ohlcv_df, grades_df, on="DATE")

print(combined_df.head())

Now you can run simulations, build analytics dashboards, or train your own models.

⚙️ Endpoint Coverage for Python Devs

  • /daily-ohlcv: Historical price data
  • /trader-grades: AI signal grades (0–100)
  • /trading-signals: Bullish/Bearish signals for short and long positions.
  • /sentiment: AI-modeled sentiment scores
  • /tmai: Ask questions in plain English

All endpoints return structured JSON and can be queried via requests, axios, or any modern client.

🧠 Developer Tips

  • Each request = 1 credit (tracked in real time)
  • Rate limits depend on your plan (Free = 1 req/min)
  • Use the API Usage Dashboard to monitor and optimize
  • Free plan = 5,000 calls/month — perfect for testing and building MVPs

💸 Bonus: Save 35% with $TMAI

You can reduce your API bill by up to 35% by staking and paying with Token Metrics’ native token, $TMAI. Available via the settings → payments page.

🌐 Final Thoughts

If you're searching for the best python crypto price API with more than just price data, Token Metrics is the ultimate choice. It combines market data with proprietary AI intelligence, trader/investor grades, sentiment scores, and backtest-ready endpoints—all in one platform.

✅ Real-time & historical data
✅ RESTful endpoints
✅ Python-ready SDKs and docs
✅ Free plan to start building today

Start building today → tokenmetrics.com/api

Looking for SDK docs? Explore the full Python Quick Start Guide

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