Back to blog
Research

What is the Difference Between Solidity and Vyper? Complete 2025 Guide

Explore the key differences between Solidity and Vyper for Ethereum smart contracts, and learn how to choose the right language for your project in 2025.
Token Metrics Team
7
Want Smarter Crypto Picks—Free?
See unbiased Token Metrics Ratings for BTC, ETH, and top alts.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
 No credit card | 1-click unsubscribe

Smart contracts have revolutionized the blockchain ecosystem, enabling self-executing code that automatically enforces agreed-upon terms and conditions. As decentralized applications continue growing in sophistication and value, the programming languages used to create these contracts become increasingly critical. Two languages dominate Ethereum smart contract development: Solidity and Vyper. Token Metrics.

Understanding Smart Contract Languages

Before diving into Solidity vs Vyper comparison, it's essential to understand what smart contract languages do and why they matter. Smart contracts are programs that run on blockchain platforms like Ethereum, executing predetermined actions when specific conditions are met. These contracts facilitate secure, transparent, and trustless interactions between parties, eliminating intermediaries and enhancing efficiency.

Smart contract languages enable developers to define the logic and behavior of these contracts, which are immutable and executed on the blockchain. By leveraging smart contract languages, businesses can automate processes including supply chain management, financial transactions, governance systems, and much more.

High-Level vs Low-Level Languages

Smart contract programming requires converting human-readable code into machine-executable bytecode that the Ethereum Virtual Machine (EVM) can process. Developers must first choose between high-level and low-level languages based on their use case and expertise.

High-level languages abstract away granular implementation details, allowing developers to create smart contracts without deep bytecode knowledge. Solidity and Vyper are both high-level languages designed for EVM-compatible blockchains, making them accessible to developers from traditional programming backgrounds.

After compilation, both Solidity and Vyper smart contracts execute using the same bytecode language, meaning they can be used concurrently in the same application despite their different source code appearances.

Solidity: The Industry Standard

Solidity is the most widely used programming language for developing smart contracts on the Ethereum blockchain and EVM-compatible chains. Designed specifically for blockchain applications, Solidity enables developers to create secure, decentralized, and automated agreements that run on distributed networks.

Origins and Design Philosophy

Proposed by Ethereum CTO Gavin Wood, Solidity was developed to meet demand for a flexible smart contract-based developer platform. The language draws heavily on inspiration from C++, JavaScript, and Python, making it familiar to developers from various programming backgrounds.

Solidity is a high-level, Turing-complete, statically typed language where developers must explicitly declare variable types. This allows the compiler to have knowledge of data types, ensuring deterministic application behavior—a critical requirement for blockchain applications where predictability is paramount.

Key Features of Solidity

  • Object-Oriented Programming: Supports inheritance, libraries, and complex data structures for sophisticated smart contracts with reusable components.
  • Rich Feature Set: Includes function overloading, multiple inheritance, user-defined types, and complex data structures.
  • Extensive Ecosystem: Benefits from a large community support, documentation, and development tools like Remix, Hardhat, and Foundry.
  • Blockchain-Specific Commands: Built-in commands for addresses, transactions, and block data interactions.
  • Wide Adoption: Most Ethereum projects, including Uniswap, Aave, and OpenSea, are developed using Solidity.

Advantages of Solidity

  • Market Dominance: Secures 87% of DeFi TVL, making it the dominant language for decentralized finance.
  • Robust Tooling: Mature ecosystem with testing, debugging, and analysis tools.
  • Versatility: Enables implementation of complex protocols, financial instruments, and governance procedures.
  • Learning Resources: Abundant tutorials, courses, and community support.

Disadvantages of Solidity

  • Security Vulnerabilities: Increased attack surface with risks like reentrancy and integer overflows, requiring thorough audits.
  • Complexity: Extensive features can lead to harder-to-audit contracts and hidden vulnerabilities.
  • Steeper Learning Curve: Requires understanding blockchain-specific security considerations.

Vyper: The Security-First Alternative

Vyper is a contract-oriented programming language that targets the EVM with a focus on security, simplicity, and auditability. Introduced in 2018 by Ethereum co-founder Vitalik Buterin, Vyper was specifically developed to address security issues prevalent in Solidity.

Design Philosophy: Security Through Simplicity

Vyper's fundamental philosophy is that security comes from simplicity and readability. The language intentionally limits features and enforces stricter syntax to make contracts more secure and easier to audit. By reducing what’s possible, Vyper minimizes opportunities for mistakes and vulnerabilities.

Using Pythonic syntax—hence the serpentine name—Vyper code prioritizes readability so developers can easily detect bugs and vulnerabilities before deploying contracts. This approach makes code auditable by humans, not just machines.

Key Features of Vyper

  • Python-Like Syntax: Familiar for Python developers, with indentation-based structure and clear syntax.
  • Security-First Design: Eliminates object-oriented features, such as inheritance and function overloading, to reduce attack vectors.
  • Strong Typing: Variables require explicit type declaration, catching errors early.
  • Bounds Checking & Overflow Protection: Built-in safety features prevent common vulnerabilities.
  • Decidability & Gas Optimization: Ensures predictable gas consumption and avoids infinite loops, making contracts more efficient.

Advantages of Vyper

  • Enhanced Security: Designed specifically to prevent common vulnerabilities, leading to more secure contracts.
  • Readable & Audit-Friendly: Clear syntax facilitates quicker reviews and lower audit costs.
  • Concise Code: Fewer lines and simpler syntax streamline contract development.
  • Python Background: Eases onboarding for Python programmers.
  • Potential Gas Savings: Simple design can lead to more efficient contracts in specific cases.

Disadvantages of Vyper

  • Limited Adoption: Only about 8% of DeFi TVL, with a smaller ecosystem and community.
  • Fewer Features: Lack of inheritance, modifiers, and function overloading limits architectural options.
  • Smaller Tooling Ecosystem: Development tools and libraries are less mature compared to Solidity.
  • Less Industry Traction: Major projects predominantly use Solidity, limiting existing examples for Vyper development.

Differences: Solidity vs Vyper

  • Syntax & Structure: Solidity resembles JavaScript and C++, with curly braces and semicolons; Vyper uses Python-like indentation and syntax, omitting object-oriented features.
  • Feature Completeness: Solidity offers inheritance, modifiers, and dynamic data structures; Vyper is minimalist, focusing on security with fixed-size arrays and no inheritance.
  • Security Approach: Solidity relies on developer diligence and testing; Vyper enforces limitations to inherently prevent vulnerabilities.
  • Development Philosophy: Solidity emphasizes flexibility, while Vyper emphasizes security and auditability.

Choosing Between Solidity and Vyper

The decision depends on project needs, team expertise, and security priorities. Large, feature-rich DeFi protocols and complex dApps typically require Solidity's extensive capabilities. Conversely, systems demanding maximum security, or contracts that need to be highly auditable, may benefit from Vyper’s simplicity and security-focused design.

Many projects effectively combine both, using Vyper for security-critical core components and Solidity for peripheral features. This hybrid approach leverages the strengths of each language.

Leveraging Token Metrics for Smart Contract Analysis

While understanding the distinctions between Solidity and Vyper is valuable for developers, investors should also evaluate the projects' underlying code quality, security track record, and development activity. Token Metrics offers AI-powered analytics that examine code repositories, audit statuses, and project activity levels.

The platform reviews security vulnerabilities, audit history, and real-time security incidents, providing a comprehensive view that helps identify projects with strong technical foundations, regardless of their chosen language.

Furthermore, Token Metrics tracks project development activity via GitHub, helping gauge ongoing commitment and progress. Market intelligence and performance analysis reveal success patterns and areas of risk, supporting informed decision-making.

Token Metrics assists investors in balancing portfolios across projects built with different languages, offering risk assessments and alerts that enhance proactive management amid evolving blockchain security landscapes.

The Future of Smart Contract Languages

Both Solidity and Vyper are actively evolving to meet new challenges and security needs. Solidity continues enhancing security features, error handling, and optimization, driven by its large ecosystem. Vyper development emphasizes expanding capabilities while maintaining its core security principles.

Emerging languages and cross-language development strategies are beginning to complement established techniques. Combining secure core contracts in Vyper with the flexibility of Solidity is an increasingly common pattern.

Best Practices for Smart Contract Development

  • Thorough Testing: Implement comprehensive testing, including formal verification and audits, before deployment.
  • Security Audits: Engage reputable security firms to review code vulnerabilities.
  • Continuous Monitoring: Use platforms like Token Metrics for real-time risk detection post-deployment.
  • Upgradeability: Adopt upgrade patterns that allow fixing issues without losing funds or functionality.

Conclusion: Making the Right Choice

Solidity and Vyper offer distinct approaches to smart contract development. Solidity’s comprehensive features and robust ecosystem make it suitable for complex, feature-rich applications. Vyper's security-oriented, Python-like syntax is ideal for systems where auditability, simplicity, and security are top priorities.

Both languages will continue to play vital roles throughout 2025, with many projects adopting hybrid strategies. Evaluating project needs, security considerations, and team expertise will guide optimal language selection. AI analytics platforms like Token Metrics provide critical insights to support this decision, ensuring better understanding and risk management in the ever-evolving ecosystem.

Build Smarter Crypto Apps &
AI Agents in Minutes, Not Months
Real-time prices, trading signals, and on-chain insights all from one powerful API.
Grab a Free API Key
About Token Metrics
Token Metrics: AI-powered crypto research and ratings platform. We help investors make smarter decisions with unbiased Token Metrics Ratings, on-chain analytics, and editor-curated “Top 10” guides. Our platform distills thousands of data points into clear scores, trends, and alerts you can act on.
30 Employees
analysts, data scientists, and crypto engineers
Daily Briefings
concise market insights and “Top Picks”
Transparent & Compliant
Sponsored ≠ Ratings; research remains independent
Want Smarter Crypto Picks—Free?
See unbiased Token Metrics Ratings for BTC, ETH, and top alts.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
 No credit card | 1-click unsubscribe
Token Metrics Team
Token Metrics Team

Recent Posts

Announcements

Token Metrics Launches $200K Grant Program to Back Crypto Builders

Token Metrics Team
8 min

In an era where crypto is moving faster than ever, the next generation of innovation will be driven by bold builders who fuse AI with blockchain. Whether it’s a project that analyzes sentiment across the market, scores tokens with precision, or generates real-time trading signals—Token Metrics is here to fund the future.

That’s why we’re excited to announce the Token Metrics $200K Grant Program — a bold initiative to empower crypto innovators at any stage.

💾 Why We’re Launching This Grant

Crypto innovation has always thrived on open experimentation. But we know firsthand how tough it can be to go from idea to product. You need the right tools, data, support, and—yes—capital.

We’re opening the doors to all Web3 builders, researchers, hackers, and startup teams with one goal: to supercharge the creation of AI-powered crypto tools that change the game.

If you're building anything in:

  • Crypto market intelligence
  • Sentiment analysis
  • Token scoring systems
  • AI trading bots
  • On-chain analytics
  • DeFi strategy tools


then this program is for you.

🎁 What You Get

Here’s what each selected project receives:

✅ Up to $5,000 in Grants

No strings attached. We’re offering non-dilutive microgrants to help you push your project forward—whether it's hosting costs, engineering hours, or marketing.

✅ Free Access to Token Metrics API

You’ll get direct access to our AI-powered crypto data platform, including investor and trader grades, signal alerts, technical indicators, and more. Build with institutional-grade tools.

✅ Technical Support and Mentorship

Our engineering and product team is on standby to help you with integration, use cases, and product guidance. Get real feedback from people who live and breathe crypto trading and AI.

✅ Community of Builders

You’ll join a thriving ecosystem of developers, analysts, and AI tinkerers who are all solving similar challenges. Share feedback, collaborate, and level up together.

🛠 Who Can Apply?

The grant is open to all stages of projects:

  • 💡 Idea Stage – Have an idea and a plan to build? You’re eligible.
  • đŸ§Ș Beta/Prototype – Already building and testing? Let’s accelerate you.
  • 🚀 Launched Product – Need support to scale? We’re here for it.
  • 💰 Paying Users – Time to expand? We can help you get there faster.

No matter your background, location, or company size—if you’re building something innovative at the intersection of crypto + AI, we want to hear from you.

🌐 What You Can Build with the Token Metrics API

The possibilities are vast. Some ideas we’d love to see:

  • AI-powered Token Rating Tools – Use our Trader and Investor Grades to generate insights.
  • Crypto Sentiment Dashboards – Analyze and visualize market sentiment.
  • Trading Signal Generators – Build bots or dashboards using our buy/sell indicators.
  • Risk Analysis Engines – Combine our technical metrics with your models.
  • DeFi Portfolio Managers – Use our price predictions and volatility data to manage risk.
  • Educational Crypto Apps – Leverage our AI grades to teach users how to DYOR.

Want to create something we haven’t thought of? Even better.

📆 Timeline & Application

The $200K will be distributed over multiple rounds across 2025, with applications reviewed on a rolling basis.

Apply once and you’ll be considered for current and upcoming rounds.

Deadline: First batch review begins July 15, 2025.

👉 Apply here now

đŸ€ Why Build with Token Metrics?

At Token Metrics, we believe the future of investing is intelligent, data-driven, and decentralized. That’s why we’re opening up our core infrastructure—so you can build tools that make crypto smarter for everyone.

We’ve spent years perfecting our AI models, data pipelines, and trading signals. Now, we’re putting that power in your hands.

Whether you’re a student hacking on weekends, a startup looking for product-market fit, or a solo dev with a bold vision—we want to help you win.

🚀 Let’s Build the Future

This isn’t just a grant—it’s a launchpad.

With $5K in non-dilutive funding, direct access to cutting-edge crypto data, and a community of top-tier builders, you’ll have everything you need to bring your project to life.

The next breakthrough tool might be yours. All it takes is one application.

🔗 Ready to apply? Click here → https://forms.gle/T3WGexLdGr9nF1hj9

Let’s build the future of crypto—together.‍

The Token Metrics Team

Research

Crypto Index Fund: How AI Is Revolutionizing Crypto Index Investment

Token Metrics Team
8 min

The Rise of Crypto Index Funds

As the cryptocurrency market matures, investors are increasingly seeking structured and diversified ways to participate without picking individual tokens. Just as index funds transformed traditional finance, crypto index funds are reshaping digital asset investing. These funds allow investors to gain broad exposure to the crypto market through a single investment vehicle, making them a compelling choice for both new and experienced participants.

But in a fast-moving, data-heavy environment like crypto, efficiency is everything. This is where AI-enhanced crypto index investment comes in—offering smarter rebalancing, risk management, and data-driven selection strategies that outperform traditional index methodologies.

What Are Crypto Index Funds?

A crypto index fund is a digital asset investment product that tracks the performance of a group of cryptocurrencies, typically weighted by market capitalization, theme, or other quantitative factors. Similar to traditional index funds in equities (like the S&P 500), a crypto index aggregates tokens into a single, trackable basket, allowing investors to diversify easily.

Key Features of Crypto Index Funds:

  • Diversification: Spread risk across multiple crypto assets.
  • Passive Investment: No need to actively trade or research individual tokens.
  • Low Fees: Typically lower management costs than hedge funds or active trading.
  • Rebalancing: Regular updates to maintain target weights and asset mix.
  • Transparency: Index compositions and methodologies are usually public.

Popular Crypto Index Themes:

  • Top 10 or Top 25 by Market Cap
  • DeFi Index: Includes projects like Uniswap, Aave, Compound.
  • AI Tokens Index: Focused on artificial intelligence crypto projects.
  • NFT Index: Tracks platforms like Blur, Rarible, or OpenSea tokens.
  • Meme Coin Index: A speculative basket for high-risk investors.

Why Crypto Index Investment Is Gaining Popularity

Crypto markets are volatile, fast-moving, and often driven by unpredictable narratives. Many investors, especially institutions or those new to the space, are uncomfortable managing a portfolio of dozens of altcoins. That’s where crypto index investment provides a safe entry point.

Benefits of Crypto Index Funds:

  1. Reduced Volatility: Spreading capital over multiple assets cushions against extreme swings.
  2. Time-Saving: Investors don’t have to stay glued to charts or news.
  3. Risk Management: Poor performers get phased out during rebalancing.
  4. Benchmarking: Investors can measure their returns against established crypto indices.

The Problem with Traditional Crypto Index Funds

Despite their advantages, most crypto index funds still rely on static rule sets:

  • Fixed Rebalancing Intervals: Usually monthly or quarterly, which may not align with real-time market shifts.
  • Market Cap Bias: Overexposure to large-cap tokens can dilute exposure to high-growth assets.
  • No Signal Integration: They ignore on-chain activity, social sentiment, or developer metrics.

In a market as dynamic as crypto, these limitations mean missed opportunities and reduced alpha.

Enter AI: The Future of Efficient Crypto Index Funds

AI is revolutionizing how crypto indices are built, managed, and optimized. By ingesting real-time data from hundreds of sources, AI-powered systems can outperform static, rules-based indices in terms of returns, risk mitigation, and adaptability.

How AI Enhances Crypto Index Investment:

  1. Dynamic Rebalancing Based on Signals
    • Instead of rigid monthly rebalancing, AI uses market signals (e.g., momentum, trend strength, liquidity) to adjust allocations daily or even hourly.
    • Example: Exiting meme tokens during a bearish shift, reallocating to AI tokens gaining traction.
  2. Sentiment Analysis and News Detection
    • AI scans Twitter, Reddit, Telegram, and news sites for bullish/bearish sentiment, helping identify trends before they go mainstream.
    • This is crucial for niche tokens with limited historical data.
  3. On-Chain Metrics and Smart Contract Activity
    • AI monitors transaction volumes, active wallets, staking ratios, and developer commits to detect growth or decline before prices reflect it.
  4. Risk-Adjusted Weighting Models
    • Rather than simply weighting by market cap, AI uses volatility, Sharpe ratio, and correlation models to dynamically assign weights.
    • This reduces overexposure to volatile assets and boosts overall portfolio efficiency.
  5. Backtesting and Optimization
    • AI can simulate thousands of portfolio combinations over historical data to find optimal strategies based on the user’s risk profile.

Real-World Example: AI-Driven Crypto Index Platforms

Some platforms are already pioneering AI-powered crypto indices:

  • Token Metrics AI Indices: Combine machine learning with market sentiment to allocate and rebalance crypto portfolios automatically. They feature bullish and bearish signals that guide when to enter or exit an index.
  • Bitwise & Galaxy Indices: Though more traditional, they’re beginning to explore data-driven rebalancing and smart beta strategies.
  • DeFi Pulse Index (DPI): A static sector index for DeFi, but when enhanced with AI (e.g., incorporating protocol usage data), it could evolve into a dynamic performer.

The Future: Personalized AI Crypto Index Funds

Imagine a world where your crypto portfolio isn’t just passively tracking a fixed list—but actively evolving based on your risk profile, market trends, and even your trading behavior.

AI will enable:

  • User-Customized Indices: Choose themes (e.g., AI, RWA, Gaming) and let AI build and manage the ideal mix.
  • Automated Exit Strategies: AI detects early warning signals and reallocates your funds to stablecoins.
  • Goal-Based Investing: AI manages your crypto portfolio to hit a target (e.g., 15% annualized return or reduce drawdowns under 10%).

Final Thoughts: Best Crypto Index Investing Starts with AI

Crypto index funds offer a powerful solution for investors looking to simplify their entry into the world of digital assets. But in a space defined by speed, volatility, and complexity, static methods are quickly becoming outdated.

By incorporating AI into crypto index investment, the future becomes more adaptive, predictive, and personalized. Whether you're a passive investor or an active trader looking for an edge, AI-powered crypto indices are unlocking a new frontier in digital wealth creation.

Announcements

Build the Future of Crypto Trading: Integrating Token Metrics with LangChain for Smarter Crypto Decisions

Token Metrics Team
8 min

The rise of AI in crypto trading has opened new frontiers, and Token Metrics is leading the charge by enabling developers to build intelligent trading agents using its powerful API. The latest innovation? A seamless integration with LangChain – a popular framework for building context-aware agents using large language models (LLMs). In this blog post, we’ll break down how this integration works, what it enables, and why it represents a game-changing leap in automated crypto analysis.

What is LangChain?

LangChain is an open-source framework that helps developers build applications powered by large language models like Gemini, Claude, and OpenAI. It enables developers to build a wide range of advanced AI solutions, including:

  • Conversational agents
  • Retrieval-based question answering
  • Tool-using AI agents
  • Autonomous decision-making bots

By providing a flexible structure, LangChain makes it easy to integrate LLMs with real-world data sources and external tools, empowering your application to both reason and take action.

What is the Token Metrics API?

The Token Metrics API is a rich data layer for crypto investors, analysts, and builders. It provides real-time and historical data across:

  • AI-powered Trader and Investor Grades
  • Daily/Hourly OHLCV metrics
  • Bullish/Bearish AI signals
  • Quantitative indicators
  • Curated Crypto Indices

With over 80 data points per token and robust filtering, the API makes it easy to identify profitable tokens, spot market trends, and build intelligent trading strategies.

Why Combine LangChain and Token Metrics?

Combining LangChain with Token Metrics lets you build AI-powered crypto agents that deliver market analysis and actionable insights. These agents can:

  • Analyze crypto prices, trends, and sentiment using AI-driven methods
  • Apply predefined strategies or custom logic for automated decision making
  • Generates clear, human-readable insights and trading signals
  • Identify and highlight tokens with strong profit potential

This integration equips your crypto applications with intelligent, data-driven capabilities to support smarter trading and research.

Getting Started: Building the Agent

The integration process begins with cloning a GitHub repository (public upon video release), which includes everything needed to run a Token Metrics x LangChain demo agent. After installing the dependencies and opening the codebase in a code editor, you’ll find a fully documented README that walks you through the setup.

Step 1: Install Dependencies 

Navigate to the project directory and install the required packages using:

‍

Step 2: Configure Environment Variables

Before spinning up the agent, add your Token Metrics API key and your LLM API key (Openai, gemini, etc..) to the .env file. These credentials authorize the agent to access both Token Metrics and your chosen LLM.

Step 3: Define and Run the Agent 

The agent logic is explained directly in the README and starter code sample, making it easy to follow and customize. You’ll find clear instructions and code snippets that guide you through setting up the agent’s capabilities.

The agent supports two main modes:

  • Simple Agent: A straightforward agent that answers user questions using Token Metrics tools. It’s ideal for quick queries and basic crypto research tasks.
  • Advanced Agent: A more powerful agent capable of reasoning through complex tasks, chaining together multiple tools, and providing deeper analysis. This agent can handle multi-step queries and deliver more comprehensive insights.

Powered by LangChain’s ReAct (Reasoning + Acting) framework, your agent can:

  • Access a suite of Token Metrics tools for crypto analysis, including price data, trading signals, grades, and sentiment
  • Apply predefined strategies or custom logic for automated decision-making
  • Generate clear, human-readable insights and trading signals
  • Filter and highlight tokens based on objective, data-driven criteria

With comprehensive documentation and step-by-step guidance in the README, you can quickly build, customize, and deploy your own intelligent crypto research assistant—no separate agent.py file required.

A Real-World Example: Finding Winning Tokens

Here’s how the agent works in practice:

  • It queries tokens with a valid Trader Grade
  • Filters tokens with Bullish AI signals
  • Compares Trading Signal ROI vs Holding ROI
  • Filters out tokens that aren’t outperforming with active trading

In the test case, it identifies BANANAS S31 as a top candidate:

  • High trader grade
  • Bullish signal
  • Strong Trading Signal ROI (better than holding)

At the end of its analysis, the bot outputs a summary of:

  • Overall market sentiment
  • Top token opportunities
  • Macro-level recommendations

In this case, while BANANAS S31 stood out, the overall market leaned neutral with a slight long-term bearish bias, a useful snapshot for any trader.

Switching to the Advanced Agent

LangChain’s flexibility allows the same bot to switch into an interactive chatbot by attaching memory to the agent. Users can now type in:

“What are the top 3 tokens to watch today?”
“Is the market bullish or bearish?”
“Give me DeFi tokens with bullish signals.”

The agent can dynamically select and chain together specialized crypto analysis tools in response to your questions. This means the agent doesn’t just answer queries with static information but it actively pulls the latest Token Metrics data, applies AI-driven analytics, and synthesizes insights using multiple sources and methods. 

As a result, you will get clear, context-aware responses about market trends, trading signals, token performance, and more. All grounded by the Token Metrics APIs

Key Benefits of This Integration

Here’s why this LangChain x Token Metrics setup is a big deal:

✅ AI That Acts

LangChain agents go beyond conversation—they can autonomously scan and analyze crypto markets using a suite of Token Metrics tools.

✅ Actionable Data

Token Metrics transforms complex market data into actionable insights, empowering the agent to support smarter trading and investment decisions.

✅ Current Market Analysis

Every time the agent runs, it draws on up-to-date Token Metrics data, ensuring responses reflect the latest market conditions.

✅ Fully Customizable

Tailor the agent to your needs, filter by DeFi tokens, set custom ROI thresholds, or incorporate additional data sources like social sentiment. The open-source codebase makes it easy to adapt the agent for any use case

What Can You Build With This?

This framework provides a versatile foundation for a wide range of crypto applications, including:

  • Personal trading assistants
  • Crypto Telegram bots
  • LLM-integrated crypto dashboards
  • Quant strategy testers
  • AI-powered newsletters and daily briefs

By combining a powerful API with a reasoning engine, you unlock a new frontier in crypto intelligence.

Final Thoughts

The integration of Token Metrics with LangChain shows what’s possible when deep crypto analytics meets autonomous reasoning. Instead of flipping between dashboards, you can build an agent that does the research for you, surfaces profitable tokens, and delivers daily alpha—automatically.

Whether you’re a developer, trader, or AI enthusiast, this setup gives you a robust foundation to experiment, build, and push the future of AI trading forward.

Try It Yourself

Once the repository is public, you’ll be able to:

  • Clone it from GitHub
  • Add your API keys
  • Customize your agent
  • Start generating automated crypto insights today

Click here to view the demo.

AI agents are the future of trading—and with Token Metrics and LangChain, the future is already here.

Choose from Platinum, Gold, and Silver packages
Reach with 25–30% open rates and 0.5–1% CTR
Craft your own custom ad—from banners to tailored copy
Perfect for Crypto Exchanges, SaaS Tools, DeFi, and AI Products