Announcements

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

A seamless integration with LangChain – a popular framework for building context-aware agents using large language models (LLMs).
Token Metrics Team
8 min
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.

Build Smarter Crypto Apps &
AI Agents in Minutes, Not Months
Real-time prices, trading signals, and on-chain insights all from one powerful API.
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Token Metrics Team
Token Metrics Team

Recent Posts

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

Research

Crypto API to Google Sheets in 5 Minutes: How to Use Token Metrics API with Apps Script

Token Metrics Team
6 min
MIN

If you're a trader, data analyst, or crypto enthusiast, chances are you've wanted to pull live crypto data directly into Google Sheets. Whether you're tracking prices, building custom dashboards, or backtesting strategies, having real-time data at your fingertips can give you an edge.

In this guide, we'll show you how to integrate the Token Metrics API — a powerful crypto API with free access to AI-powered signals — directly into Google Sheets in under 5 minutes using Google Apps Script.

📌 Why Use Google Sheets for Crypto Data?

Google Sheets is a flexible, cloud-based spreadsheet that:

  • Requires no coding to visualize data
  • Can be shared and updated in real time
  • Offers formulas, charts, and conditional formatting
  • Supports live API connections with Apps Script

When combined with the Token Metrics API, it becomes a powerful dashboard that updates live with Trader Grades, Bull/Bear Signals, historical OHLCV data, and more.

🚀 What Is Token Metrics API?

The Token Metrics API provides real-time and historical crypto data powered by AI. It includes:

  • Trader Grade: A score from 0 to 100 showing bullish/bearish potential
  • Bull/Bear Signal: A binary signal showing market direction
  • OHLCV: Open-High-Low-Close-Volume price history
  • Token Metadata: Symbol, name, category, market cap, and more

The best part? The free Basic Plan includes:

  • 5,000 API calls/month
  • Access to core endpoints
  • Hourly data refresh
  • No credit card required

👉 Sign up for free here

🛠️ What You’ll Need

  • A free Token Metrics API key
  • A Google account
  • Basic familiarity with Google Sheets

⚙️ How to Connect Token Metrics API to Google Sheets

Here’s how to get live AI-powered crypto data into Sheets using Google Apps Script.

🔑 Step 1: Generate Your API Key

  1. Visit: https://app.tokenmetrics.com/en/api
  2. Click “Generate API Key”
  3. Copy it — you’ll use this in the script

📄 Step 2: Create a New Google Sheet

  1. Go to Google Sheets
  2. Create a new spreadsheet
  3. Click Extensions > Apps Script

💻 Step 3: Paste This Apps Script

const TOKEN_METRICS_API_KEY = 'YOUR_API_KEY_HERE';

async function getTraderGrade(symbol) {

  const url = `https://api.tokenmetrics.com/v2/trader-grades?symbol=${symbol.toUpperCase()}`;

  const options = {

    method: 'GET',

    contentType: 'application/json',

    headers: {

      'accept': 'application/json',

      'x-api-key': TOKEN_METRICS_API_KEY,

    },

    muteHttpExceptions: true

  };

  

  const response = UrlFetchApp.fetch(url, options);

  const data = JSON.parse(response.getContentText() || "{}")

  

  if (data.success && data.data.length) {

    const coin = data.data[0];

    return [

      coin.TOKEN_NAME,

      coin.TOKEN_SYMBOL,

      coin.TA_GRADE,

      coin.DATE

    ];

  } else {

    return ['No data', '-', '-', '-'];

  }

}

async function getSheetData() {

  const sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();

  const symbols = sheet.getRange('A2:A').getValues().flat().filter(Boolean);

  const results = [];

  results.push(['Name', 'Symbol', 'Trader Grade', 'Date']);

  for (const symbol of symbols) {

    if (symbol) {

      const row = await getTraderGrade(symbol);

      results.push(row);

    }

  }

  sheet.getRange(2, 2, results.length, results[0].length).setValues(results);

}

🧪 Step 4: Run the Script

  1. Replace 'YOUR_API_KEY_HERE' with your real API key.
  2. Save the project as TokenMetricsCryptoAPI.
  3. In your sheet, enter a list of symbols (e.g., BTC, ETH, SOL) in Column A.
  4. Go to the script editor and run getSheetData() from the dropdown menu.

Note: The first time, Google will ask for permission to access the script.

✅ Step 5: View Your Live Data

After the script runs, you’ll see:

  • Coin name and symbol
  • Trader Grade (0–100)
  • Timestamp

You can now:

  • Sort by Trader Grade
  • Add charts and pivot tables
  • Schedule automatic updates with triggers (e.g., every hour)

🧠 Why Token Metrics API Is Ideal for Google Sheets Users

Unlike basic price APIs, Token Metrics offers AI-driven metrics that help you:

  • Anticipate price action before it happens
  • Build signal-based dashboards or alerts
  • Validate strategies against historical signals
  • Keep your data fresh with hourly updates

And all of this starts for free.

🏗️ Next Steps: Expand Your Sheet

Here’s what else you can build:

  • A portfolio tracker that pulls your top coins’ grades
  • A sentiment dashboard using historical OHLCV
  • A custom screener that filters coins by Trader Grade > 80
  • A Telegram alert system triggered by Sheets + Apps Script + Webhooks

You can also upgrade to the Advanced Plan to unlock 21 endpoints including:

  • Investor Grades
  • Smart Indices
  • Sentiment Metrics
  • Quantitative AI reports
  • 60x API speed

🔐 Security Tip

Never share your API key in a public Google Sheet. Use script-level access and keep the sheet private unless required.

🧩 How-To Schema Markup (for SEO)

{

  "@context": "https://schema.org",

  "@type": "HowTo",

  "name": "Crypto API to Google Sheets in 5 Minutes",

  "description": "Learn how to connect the Token Metrics crypto API to Google Sheets using Google Apps Script and get real-time AI-powered signals and prices.",

  "totalTime": "PT5M",

  "supply": [

    {

      "@type": "HowToSupply",

      "name": "Google Sheets"

    },

    {

      "@type": "HowToSupply",

      "name": "Token Metrics API Key"

    }

  ],

  "tool": [

    {

      "@type": "HowToTool",

      "name": "Google Apps Script"

    }

  ],

  "step": [

    {

      "@type": "HowToStep",

      "name": "Get Your API Key",

      "text": "Sign up at Token Metrics and generate your API key from the API dashboard."

    },

    {

      "@type": "HowToStep",

      "name": "Create a New Google Sheet",

      "text": "Open a new sheet and list crypto symbols in column A."

    },

    {

      "@type": "HowToStep",

      "name": "Add Apps Script",

      "text": "Go to Extensions > Apps Script and paste the provided code, replacing your API key."

    },

    {

      "@type": "HowToStep",

      "name": "Run the Script",

      "text": "Execute the getSheetData function to pull data into the sheet."

    }

  ]

}

✍️ Final Thoughts

If you're serious about crypto trading or app development, integrating live market signals into your workflow can be a game-changer. With the Token Metrics API, you can get institutional-grade AI signals — right inside Google Sheets.

This setup is simple, fast, and completely free to start. Try it today and unlock a smarter way to trade and build in crypto.

👉 Get Your API Key & Start for Free

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