Crypto Basics

Cardano (ADA) Crypto – What It Is and How It Works?

Learn everything about Cardano (ADA) crypto and how it works in this descriptive guide.
Token Metrics Team
8 minutes
MIN

Cardano (ADA) can be described as a blockchain platform that’s designed to enable the development of decentralized applications and smart contracts. It is the first blockchain platform to be built on a scientific philosophy and to be developed through peer-reviewed research and scientific rigor. Developed by a global team of leading researchers and engineers, Cardano is set to revolutionize the way we use and interact with blockchain technology. 

This beginner's guide to Cardano will provide you with all the information you need to understand the platform, its features, and how to use it. From its unique consensus algorithm to its native token ADA, this guide will provide you with a comprehensive overview of Cardano. Whether you're a beginner interested in learning more about Cardano or a blockchain expert looking for the latest information, this guide has you covered from end-to-end. 

History of Cardano

Cardano was founded by Charles Hoskinson, who also co-founded Ethereum. However, Cardano is a very different platform from Ethereum regarding its design and goals. Whereas Ethereum is a decentralized application ("dapp") platform designed to power all sorts of different decentralized applications, Cardano is designed to be a "first generation" blockchain platform that can be used to build decentralized applications, as well as other things.

The Cardano Foundation, IOHK, and Emurgo are developing the Cardano platform. The three groups are working together to build the Cardano platform and will hold a stake in the Cardano ecosystem. 

The first phase of Cardano's development began in 2015. At the time, a company called Input-Output (IOHK) was contracted to build the platform. In 2017, IOHK decided to hand over control of the project to the Cardano Foundation and Emurgo. The three partners are now working together to bring Cardano to market. The next development phase has been completed sometime between 2020 and 2021. After that, Cardano emerged as a fully decentralized blockchain.

How Does Cardano Work?

The Cardano platform uses a proof of stake (PoS) consensus algorithm to manage its decentralized network. Proof of stake is a consensus algorithm where the right to add new blocks to the blockchain is determined not by computing power but by coin ownership. In PoS-based blockchains, users must "stake" or "deposit" their coins to add new blocks to the blockchain for a certain amount of time. The more coins a user stakes, the greater the chance that the user will be selected to add a new block. Cardano uses the Ouroboros proof of stake algorithm. 

Ouroboros is the first proof of stake algorithm to be proven secure in a peer-reviewed paper. This unique algorithm uses a "random selection of a catch-up fellow" to create a network with no central authority. In other words, no single person or group can control the network. The algorithm works by randomly selecting a "follower" who can "catch up" with the "leader."

The leader is the person responsible for adding new blocks to the blockchain. The follower has one job: to predict what the leader will do. If the follower is correct, they are promoted to the leader and given a chance to add a new block. If the follower is incorrect, they remain a follower, and another random person is selected to catch up. The Ouroboros algorithm was expected to be completed by June 2020. But, according to recent reports, Charles Hoskinson said that the Ouroboros Genesis implementation will be in 2023.

Cardano's Development and Governance

The development and governance of Cardano are handled by three large organizations:

The Cardano Foundation: The Cardano Foundation maintains Cardano's core. This group promotes the platform, manages its marketing and communications, and defends the brand.

IOHK: IOHK leads the team behind Cardano's core. This group is responsible for developing and maintaining the platform's core software and bringing new features to the market.

Emurgo: The third group, Emurgo, brings businesses and investments to the Cardano ecosystem. Emurgo helps businesses integrate with the Cardano network and encourages others to build projects on the Cardano platform.

The functioning of Cardano stands tall because of the highly secured and powerful ecosystem as mentioned above. Now, what is Cardano’s native token ADA?

Cardano's Native Token - ADA

Cardano's native token, ADA, sends money on the Cardano blockchain. It also rewards people who help maintain and build the network. The team behind Cardano has stated that ADA is more than just a token: it also serves as "the fuel that drives the Cardano ecosystem." Cardano’s development team has stated that the platform will be fully decentralized once the network has been around for a few years. Until then, the platform will be maintained by a group of stakeholders who have a vested interest in the platform's success. These stakeholders have a stake in the system and are rewarded with ADA for helping maintain the platform. 

There are 3-easy ways to earn ADA

  • Hosting a node, 
  • Providing software assurance, or 
  • Contributing to the development of Cardano's software or research.

Apart from these, Cardano’s powerful 3-layered ecosystem makes it reliable and trustworthy. 

The 3-Layered Cardano's Ecosystem

Here are the three secured-layers that constitute Cardano (ADA): 

The Cardano Network: The Cardano network is the blockchain that runs the ADA token and smart contracts. It is maintained by the stakeholders, who receive ADA for their work.

Cardano's core technology: The Cardano core represents the core software that powers the Cardano network. This includes the programming languages used to build decentralized applications and the virtual machine that runs those apps.

All the projects built on top of the Cardano platform: The Cardano projects layer lists all the decentralized applications built on top of the Cardano network.
To top it all, you can also enjoy the benefit of smart contracts on Cardano. 

Smart Contracts On Cardano

Although Cardano is designed to be a dapp platform, it can also be used to build smart contracts. The programming language used to build smart contracts on Cardano is called Haskell and Cardano's virtual machine, called the "Computing Resources And Dispatcher" (CRDD), can execute many programming languages.

Any decentralized application built in any programming language can be hosted on the Cardano network. Cardano's smart contracts are unique because they are the first to be verified by a formal verification tool called the "Industrial Strength Verification" (ISV). This tool will help you confirm whether or not a smart contract is safe to use.

Cardano's Use Cases

Use Case #1: The first use case for Cardano is a decentralized application platform. This means that developers can build apps on top of the Cardano blockchain. These dapps will be able to send and receive ADA and use other features like the ability to create a wallet or sign a transaction. 

Use Case #2: The second use case for Cardano is as a financial asset. Investors can buy and sell ADA on cryptocurrency exchanges, and the token could also represent ownership in a company.

Now, let’s see the security measures that Cardano aims to offer.

Security on Cardano

One of the most common questions about Cardano is how secure it is compared to other blockchains. Cardano does not claim to be more secure than other blockchains but seeks to be as secure as possible. The team behind Cardano has said that one of their goals is to be the "safest and most reliable blockchain." 

One way Cardano strives to be more secure is through its unique design. While other blockchains are designed to do one thing well, Cardano is designed to do many different things less well. Cardano's design means no single platform part is crucial to its operation. If one part of the platform fails, many other parts can take its place. This indicates safety at its best.

Is Cardano a Worthy Investment?

There we are swinging again to whether or not Cardano is a good investment. Let’s check out the latest updates before we decide, shall we?

According to the Cryptoglobe’s Report, ADA’s price might soar up to 100% by 31st January, 2023. Major upgrades are being anticipated by investors to improve DeFi’s significance through its oracles.

So, Cardano is something to look forward to owing to its upcoming features. 

Future of Cardano

Let’s dive a bit further into the future. Cryptopolitan thinks the price of ADA will soar up to $21.35 on an average, with a minimum price of $20.55. Changelly also believes that ADA price will rise, but the website thinks the coin price will only peak at $15.69, with an average of $13.92, similar to the data from Price Prediction. The website’s analysts predict that the coin’s maximum price will be $15.69 with a minimum of $13.55.

Most experts predict that Cardano might see a bright future in 2023. With persistent developments Cardano’s ecosystem has been witnessing, and in the crypto asset market as a whole, Cardano can potentially reach a new high.

The Bottom Line

Cardano aims to be a "first generation" blockchain technology. The platform is being built by a group of organizations, each with a specific role in the project.

The team hopes this design will help Cardano achieve its goal of being the most secure blockchain. The platform uses a unique consensus algorithm, and its native token is storable in various wallets. The token can be used to represent ownership in a company. 

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Research

APIs Explained: How They Power Apps and AI

Token Metrics Team
5
MIN

APIs are the invisible glue connecting modern software — from mobile apps and cloud services to AI agents and crypto dashboards. Understanding what an API is, how it works, and how to evaluate one is essential for builders, analysts, and product managers who need reliable data and interoperable systems. This guide breaks down APIs into practical components, shows common real-world use cases, and outlines security and integration best practices without jargon.

What an API Is and Why It Matters

API stands for "Application Programming Interface." At its core, an API is a contract between two software systems that defines how they exchange information. Instead of sharing raw databases or duplicating functionality, systems expose endpoints (URL patterns or function calls) that clients can use to request specific data or actions.

APIs matter because they enable modularity and reuse. Developers can consume services—such as authentication, payments, mapping, or market data—without rebuilding them. For example, a crypto portfolio app might fetch price feeds, on-chain metrics, and historical candles via multiple APIs rather than maintaining every data pipeline internally.

APIs also power automation and AI: machine learning models and AI agents frequently call APIs to retrieve fresh data, trigger workflows, or enrich decision-making pipelines. Tools like Token Metrics use APIs to combine price feeds, signals, and on-chain indicators into research products.

How APIs Work: Requests, Responses, and Data Formats

Most web APIs follow a simple request–response pattern over HTTP(S). A client sends a request to an endpoint and receives a response containing status information and payload data. Key elements to understand:

  • Endpoints: Specific URLs or routes that expose functionality, e.g., /v1/prices or /v1/orders.
  • Methods: HTTP verbs such as GET (read), POST (create), PUT/PATCH (update), and DELETE.
  • Authentication: API keys, OAuth tokens, or signed requests ensure only authorized clients can access certain endpoints.
  • Response codes: 200 for success, 4xx for client errors, 5xx for server errors—useful for error handling.
  • Data formats: JSON is the most common for modern APIs; XML and protocol buffers appear in legacy or high-performance systems.

Understanding these primitives helps teams design robust clients: retry logic for transient errors, pagination for large datasets, and schema validation for payload integrity.

Common Types of APIs and Real-World Use Cases

APIs come in several flavors depending on their design and purpose. Recognizing the differences helps you pick the right integration model.

  • REST APIs: Resource-oriented, stateless, and commonly use JSON. They’re widely adopted for web services.
  • GraphQL: A query language that allows clients to request only the fields they need, reducing over-fetching in complex data models.
  • WebSocket / Streaming APIs: For real-time updates (e.g., live price ticks, notifications). Useful in trading dashboards and live analytics.
  • gRPC / Protocol Buffers: High-performance binary RPCs for low-latency microservices.
  • On-chain / Blockchain APIs: Specialized endpoints that return transaction history, token balances, and contract events for blockchain analysis.

Use-case examples:

  1. A mobile app calls a REST API to authenticate users and load personalized content.
  2. An AI agent queries a streaming API to receive real-time signals for model inference (without polling).
  3. A crypto analytics platform aggregates multiple market and on-chain APIs to produce composite indicators.

Security, Rate Limits, and Best Practices for Integration

When integrating any external API, consider availability and trustworthiness alongside features. Key operational and security practices include:

  • Authentication & Secrets Management: Store API keys and tokens securely (secrets manager or environment variables), rotate credentials periodically, and avoid embedding keys in client-side code.
  • Rate Limiting & Throttling: Respect provider limits and implement exponential backoff and jitter to handle 429 responses gracefully.
  • Data Validation: Validate and sanitize incoming data to prevent schema drift or malicious payloads.
  • Monitoring & SLAs: Track error rates, latency, and uptime. Investigate providers’ SLA and status pages for critical dependencies.
  • Privacy & Compliance: Ensure data handling aligns with legal requirements and your organization’s policies, especially when personal or financial data is involved.

Selecting the right provider often requires scenario analysis: trade off latency vs. cost, historical depth vs. real-time freshness, and breadth of endpoints vs. ease of use. Well-documented APIs with client SDKs, clear versioning, and robust support reduce integration risk.

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FAQ: What is an API?

Q1: What’s the difference between an API and a web service?

An API is a broader concept: a set of rules for interacting with software. A web service is a type of API that specifically uses web protocols (HTTP) to exchange data between systems.

FAQ: How do I authenticate with an API?

Authentication methods vary: API keys for simple use cases, OAuth for delegated access, or HMAC signatures for high-security endpoints. Always follow the provider’s recommended flow and protect credentials.

FAQ: When should I use GraphQL over REST?

GraphQL is useful when clients need flexible queries and should avoid over- or under-fetching. REST is simpler and often sufficient for straightforward resource-based designs. Choose based on data complexity and client requirements.

FAQ: How do rate limits affect integrations?

Rate limits control how many requests you can make in a given window. Plan batching, caching, and backoff strategies to stay within limits while maintaining performance and reliability.

FAQ: Can APIs be used for real-time data?

Yes. Real-time needs are typically met with WebSocket or streaming APIs that push updates to clients. Polling REST endpoints frequently is possible but less efficient and may hit rate limits.

FAQ: How do I evaluate an API provider?

Look at documentation quality, authentication options, latency, historical data availability, SDKs, support channels, and uptime history. Proof-of-concept integrations and small-scale performance tests reveal practical fit.

Disclaimer

This article is educational and informational only. It does not constitute financial, legal, or investment advice. Evaluate APIs and providers based on your organization’s technical requirements, compliance needs, and risk tolerance before integrating.

Research

APIs Explained: How They Connect Apps and Data

Token Metrics Team
5
MIN

APIs power modern software by letting systems talk to one another. Whether you use a mobile app, connect a trading bot, or plug an AI model into a data feed, APIs are the plumbing that moves data and requests. This guide explains what an API is, how APIs work, common types and protocols, practical crypto and AI use cases, and design and security practices you should know as a developer or analyst.

What an API Is and How It Works

API stands for Application Programming Interface. Broadly, it is a contract that defines how one software component requests services or data from another. An API specifies:

  • Available endpoints or functions (what you can ask for)
  • Input and output formats (how to send and receive data)
  • Authentication and rate limits (who can use it and how often)

At runtime a client (for example, a web app) sends a request to an API endpoint on a server. The server validates the request, executes logic, and returns a response—usually structured data like JSON or XML. Think of an API as a standardized messenger that abstracts internal complexity and enforces clear expectations between systems.

Common API Types and Protocols

APIs differ by style and protocol. Key varieties include:

  • REST: Resource-oriented, uses HTTP methods (GET/POST/PUT/DELETE) and JSON. Widely adopted for web services.
  • GraphQL: Client-specified queries that can reduce over- or under-fetching by letting clients request exactly what they need.
  • gRPC: High-performance RPC framework using Protocol Buffers; common for internal microservices.
  • Webhooks: Server-to-client callbacks that push events instead of polling, useful for real-time notifications.

Protocol selection depends on latency, payload size, developer ergonomics, and whether the API is public, private, or internal to an organization.

APIs in Crypto and AI: Practical Use Cases

APIs are foundational in crypto and AI workflows. Examples include:

  • Market data: Endpoints that return prices, orderbook snapshots, and historical candles for trading and backtesting.
  • On-chain data: APIs that expose blockchain state, transactions, token balances, and smart contract events.
  • Execution: Trading APIs that allow order placement, cancellations, and account management (note: focus on technical integration, not trading advice).
  • AI model inputs: Data pipelines that feed structured market or on-chain data into models and agents for feature generation or monitoring.

For teams building crypto analytics or AI agents, structured and timely data is essential. For example, Token Metrics provides research tools that combine on-chain and market signals behind an API-friendly interface, illustrating how analytics platforms expose data and insights for downstream tools.

Design, Security, and Best Practices for APIs

Robust API design balances usability, performance, and safety. Key best practices include:

  1. Clear documentation: Describe endpoints, parameters, examples, and error codes to speed onboarding.
  2. Versioning: Use explicit versioning (v1, v2) to avoid breaking client integrations when you change behavior.
  3. Authentication & Authorization: Implement API keys, OAuth, or signed requests and scope keys to limit access.
  4. Rate limits & quotas: Protect backend systems and ensure fair use by enforcing sensible limits.
  5. Input validation & sanitization: Prevent injection attacks and ensure predictable behavior.
  6. Monitoring & observability: Track latency, error rates, and usage patterns to detect anomalies early.

Security is especially important for crypto-related endpoints that can expose sensitive account or on-chain actions. Design your API assuming adversaries will attempt to abuse endpoints and validate responses on the client side as well.

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FAQ: What is an API — Common Questions

How does an API differ from a library or SDK?

An API defines how to communicate with a service; a library is code you include in a project. An SDK bundles libraries, documentation, and tools to help developers use an API more easily.

What is the difference between REST and GraphQL?

REST exposes fixed endpoints for resources and often returns entire objects, while GraphQL lets clients specify exact fields to fetch. GraphQL can reduce data transfer for complex UIs but adds server-side complexity.

Are public APIs safe to use for production systems?

Public APIs can be used in production if they meet reliability, latency, and security requirements. Verify SLAs, implement retries and fallbacks, and isolate credentials using secure storage patterns.

How do I authenticate with most APIs?

Common methods include API keys, OAuth 2.0, JWTs, and signed requests. Choose mechanisms that match your threat model: short-lived tokens and scoped keys reduce exposure compared to long-lived secrets.

How can I test and monitor an API integration?

Use unit and integration tests with mocked responses, postman or curl for ad-hoc tests, and observability tools to monitor latency, error rates, and unexpected schema changes. Deploy health checks and alarming for critical endpoints.

What are typical rate limits and how should clients handle them?

Rate limits vary by provider; common patterns include requests-per-minute and burst allowances. Clients should implement exponential backoff, respect Retry-After headers, and cache responses where appropriate.

How does an API support AI agents?

APIs supply structured, machine-readable data that AI agents can ingest for feature generation, state tracking, or decision-making. Consistent schemas, timestamps, and low-latency endpoints improve model reliability.

Conclusion

APIs are the connective tissue of modern software, enabling modular design, data sharing, and integration across web, crypto, and AI systems. Understanding API types, security practices, and operational patterns helps teams design robust integrations and choose the right tooling for scale.

Disclaimer

This article is for educational purposes only. It provides technical explanations and practical guidance about APIs and related technologies. It does not constitute investment, legal, or professional advice.

Research

APIs Explained: How They Power Apps and Data

Token Metrics Team
5
MIN

APIs are one of the least visible yet most powerful pieces of modern software infrastructure. Whether you're building a mobile app, connecting to market data, or integrating an AI model, APIs are the bridges that let systems share data and functionality. This guide unpacks what an API is, how different API styles work, and practical steps to evaluate and use APIs safely and effectively.

What an API Is: A Practical Definition

An API—short for Application Programming Interface—is a set of rules and protocols that lets one software system request services or data from another. At its simplest, an API specifies the inputs a caller must provide, the format of those inputs, and the shape of the output it can expect. APIs abstract internal implementation details so developers can build on top of existing services without reinventing core functionality.

Key conceptual elements include:

  • Endpoints: Named URLs or addresses that expose specific functionality or data.
  • Requests & Responses: Standardized messages (often JSON) sent to and returned from endpoints.
  • Authentication: Mechanisms (API keys, OAuth tokens) that control who can access the interface.
  • Rate limits & quotas: Rules that protect services and ensure fair usage.

How APIs Work: The Mechanics

At a technical level, most modern APIs follow a request-response model. A client sends a request to an endpoint, the server processes that request using internal logic or data stores, and then returns a response. The most common flow includes:

  1. Client constructs a request (method, headers, body) according to the API specification.
  2. Client authenticates using the required scheme (API key, bearer token, etc.).
  3. Server validates input, applies business logic, and accesses data sources.
  4. Server returns a standardized response with status codes and a body payload.

APIs also include non-functional considerations: latency, consistency, error handling, and observability. Robust APIs document error codes, expected payloads, and examples to reduce integration friction.

Common API Types and When to Use Them

Not all APIs are the same. Choosing the right style depends on use case, performance needs, and complexity.

  • REST (Representational State Transfer): Widely used, HTTP-based, resource-oriented, typically JSON over GET/POST methods. Good for CRUD-style operations and public web services.
  • GraphQL: Client-driven queries that let callers request precisely the fields they need. Useful when reducing overfetching matters or when multiple clients require different views of the same data.
  • WebSocket: Full-duplex channels for real-time, low-latency communication. Common for live market feeds, chat systems, and push notifications.
  • RPC / gRPC: Procedure-call semantics with efficient binary serialization, often used in microservices and high-throughput internal systems.

In crypto and AI contexts, combinations are common: REST for configuration and historical data, WebSocket for live updates, and specialized RPC endpoints for blockchain node interactions.

Practical Uses, Evaluation, and Best Practices

APIs are used to access market data, execute trades (in regulated contexts), fetch on-chain metrics, call ML inference endpoints, and orchestrate microservices. When evaluating or integrating an API, consider:

  • Documentation quality: Clear examples, schemas, and code snippets shorten integration time.
  • Authentication & access models: Ensure the offered auth methods match your security needs and deployment model.
  • Rate limits and pricing: Understand throughput constraints and cost implications for production usage.
  • Data freshness and SLAs: Check update frequency, latency expectations, and uptime guarantees if available.
  • Error handling and retries: Use idempotent patterns and backoff strategies when calls fail temporarily.

For teams building AI agents or analytic dashboards, designing APIs with predictable schemas and clear versioning reduces downstream friction. AI-driven research platforms can augment manual analysis by normalizing data and providing signal overlays; for example, tools like Token Metrics integrate multiple data sources and can be accessed via APIs to feed models or dashboards.

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FAQ: What Is an API?

Q: How is an API different from a library or SDK?
A: A library is code included in an application at compile/runtime and runs locally; an SDK bundles libraries and tools for a platform. An API is an interface—often remote—that defines how to interact with a service that may run on different infrastructure.

FAQ: What security practices should I follow?

Q: How should I secure API access?
A: Use strong authentication (tokens, OAuth), enforce least privilege, rotate keys, use TLS for transport encryption, validate inputs server-side, and monitor usage for anomalies.

FAQ: What are rate limits and why do they matter?

Q: Why do APIs throttle requests?
A: Rate limits protect service stability, prevent abuse, and ensure fair access. Design clients to respect published limits and apply exponential backoff on failures.

FAQ: How do API versions work?

Q: What approaches are used for versioning?
A: Common patterns: URL versioning (/v1/...), header-based versioning, or content negotiation. Versioning maintains backward compatibility and lets providers evolve interfaces without breaking clients.

FAQ: How do I choose the right API style?

Q: REST, GraphQL, or WebSocket—how to decide?
A: Choose REST for straightforward resource access and broad compatibility, GraphQL when clients need flexible queries to minimize payloads, and WebSocket for real-time streaming or low-latency updates.

Disclaimer

This article is for informational purposes only and does not constitute financial, legal, or professional advice. It outlines technical concepts and best practices for understanding and integrating APIs. Evaluate services and compliance considerations independently before sending or acting on production data.

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