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Research
Top Crypto Trading Platforms in 2025
When it comes to crypto trading platforms, Token Metrics is not an exchange, but a crypto analytics and crypto trading intelligence platform powered by AI.
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Stop Guessing, Start Trading: The Token Metrics API Advantage
Announcements
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Big news: We’re cranking up the heat on AI-driven crypto analytics with the launch of the Token Metrics API and our official SDK (Software Development Kit). This isn’t just an upgrade – it's a quantum leap, giving traders, hedge funds, developers, and institutions direct access to cutting-edge market intelligence, trading signals, and predictive analytics.
Crypto markets move fast, and having real-time, AI-powered insights can be the difference between catching the next big trend or getting left behind. Until now, traders and quants have been wrestling with scattered data, delayed reporting, and a lack of truly predictive analytics. Not anymore.
The Token Metrics API delivers 32+ high-performance endpoints packed with powerful AI-driven insights right into your lap, including:
- Trading Signals: AI-driven buy/sell recommendations based on real-time market conditions.
- Investor & Trader Grades: Our proprietary risk-adjusted scoring for assessing crypto assets.
- Price Predictions: Machine learning-powered forecasts for multiple time frames.
- Sentiment Analysis: Aggregated insights from social media, news, and market data.
- Market Indicators: Advanced metrics, including correlation analysis, volatility trends, and macro-level market insights.
Getting started with the Token Metrics API is simple:
- Sign up at www.tokenmetrics.com/api.
- Generate an API key and explore sample requests.
- Choose a tier–start with 50 free API calls/month, or stake TMAI tokens for premium access.
- Optionally–download the SDK, install it for your preferred programming language, and follow the provided setup guide.
At Token Metrics, we believe data should be decentralized, predictive, and actionable.
The Token Metrics API & SDK bring next-gen AI-powered crypto intelligence to anyone looking to trade smarter, build better, and stay ahead of the curve. With our official SDK, developers can plug these insights into their own trading bots, dashboards, and research tools – no need to reinvent the wheel.
Token Metrics API
Moonshots API: Discover Breakout Tokens Before the Crowd
The biggest gains in crypto rarely come from the majors. They come from Moonshots—fast-moving tokens with breakout potential. The Moonshots API surfaces these candidates programmatically so you can rank, alert, and act inside your product. In this guide, you’ll call /v2/moonshots, display a high-signal list with TM Grade and Bullish tags, and wire it into bots, dashboards, or screeners in minutes. Start by grabbing your key at Get API Key, then Run Hello-TM and Clone a Template to ship fast.
What You’ll Build in 2 Minutes
- A minimal script that fetches Moonshots via /v2/moonshots (optionally filter by grade/signal/limit).
- A UI pattern to render symbol, TM Grade, signal, reason/tags, and timestamp—plus a link to token details.
- Optional one-liner curl to smoke-test your key.
- Endpoints to add next: /v2/tm-grade (one-score ranking), /v2/trading-signals / /v2/hourly-trading-signals (timing), /v2/resistance-support (stops/targets), /v2/quantmetrics (risk sizing), /v2/price-prediction (scenario ranges).
Why This Matters
Discovery that converts. Users want more than price tickers—they want a curated, explainable list of high-potential tokens. The moonshots API encapsulates multiple signals into a short list designed for exploration, alerts, and watchlists you can monetize.
Built for builders. The endpoint returns a consistent schema with grade, signal, and context so you can immediately sort, badge, and trigger workflows. With predictable latency and clear filters, you can scale to dashboards, mobile apps, and headless bots without reinventing the discovery pipeline.
Where to Find
The Moonshots API cURL request is right there in the top right of the API Reference. Grab it and start tapping into the potential!
👉 Keep momentum: Get API Key • Run Hello-TM • Clone a Template
Live Demo & Templates
- Moonshots Screener (Dashboard): A discover tab that ranks tokens by TM Grade and shows the latest Bullish tags and reasons.
- Alert Bot (Discord/Telegram): DM when a new token enters the Moonshots list or when the signal flips; include S/R levels for SL/TP.
- Watchlist Widget (Product): One-click “Follow” on Moonshots; show Quantmetrics for risk and a Price Prediction range for scenario planning.
Fork a screener or alerting template, plug your key, and deploy. Validate your environment with Hello-TM. When you scale users or need higher limits, compare API plans.
How It Works (Under the Hood)
The Moonshots endpoint aggregates a set of evidence—often combining TM Grade, signal state, and momentum/volume context—into a shortlist of breakout candidates. Each row includes a symbol, grade, signal, and timestamp, plus optional reason tags for transparency.
For UX, a common pattern is: headline list → token detail where you render TM Grade (quality), Trading Signals (timing), Support/Resistance (risk placement), Quantmetrics (risk-adjusted performance), and Price Prediction scenarios. This lets users understand why a token was flagged and how to act with risk controls.
Polling vs webhooks. Dashboards typically poll with short-TTL caching. Alerting flows use scheduled jobs or webhooks (where available) to smooth traffic and avoid duplicates. Always make notifications idempotent.
Production Checklist
- Rate limits: Respect plan caps; batch and throttle in clients/workers.
- Retries & backoff: Exponential backoff with jitter on 429/5xx; capture request IDs.
- Idempotency: De-dup alerts and downstream actions (e.g., don’t re-DM on retries).
- Caching: Memory/Redis/KV with short TTLs; pre-warm during peak hours.
- Batching: Fetch in pages (e.g., limit + offset if supported); parallelize within limits.
- Sorting & tags: Sort primarily by tm_grade or composite; surface reason tags to build trust.
- Observability: Track p95/p99, error rates, and alert delivery success; log variant versions.
- Security: Store keys in a secrets manager; rotate regularly.
Use Cases & Patterns
- Bot Builder (Headless):
- Universe filter: trade only tokens appearing in Moonshots with tm_grade ≥ X.
- Timing: confirm entry with /v2/trading-signals; place stops/targets with /v2/resistance-support; size via Quantmetrics.
- Universe filter: trade only tokens appearing in Moonshots with tm_grade ≥ X.
- Dashboard Builder (Product):
- Moonshots tab with Badges (Bullish, Grade 80+, Momentum).
- Token detail page integrating TM Grade, Signals, S/R, and Predictions for a complete decision loop.
- Moonshots tab with Badges (Bullish, Grade 80+, Momentum).
- Screener Maker (Lightweight Tools):
- Top-N list with Follow/alert toggles; export CSV.
- “New this week” and “Graduated” sections for churn/entry dynamics.
- Top-N list with Follow/alert toggles; export CSV.
- Community/Content:
- Weekly digest: new entrants, upgrades, and notable exits—link back to your product pages.
- Weekly digest: new entrants, upgrades, and notable exits—link back to your product pages.
Next Steps
- Get API Key — generate a key and start free.
- Run Hello-TM — verify your first successful call.
- Clone a Template — deploy a screener or alerts bot today.
- Watch the demo: VIDEO_URL_HERE
- Compare plans: Scale confidently with API plans.
FAQs
1) What does the Moonshots API return?
A list of breakout candidates with fields such as symbol, tm_grade, signal (often Bullish/Bearish), optional reason tags, and updated_at. Use it to drive discover tabs, alerts, and watchlists.
2) How fresh is the list? What about latency/SLOs?
The endpoint targets predictable latency and timely updates for dashboards and alerts. Use short-TTL caching and queued jobs/webhooks to avoid bursty polling.
3) How do I use Moonshots in a trading workflow?
Common stack: Moonshots for discovery, Trading Signals for timing, Support/Resistance for SL/TP, Quantmetrics for sizing, and Price Prediction for scenario context. Always backtest and paper-trade first.
4) I saw results like “+241%” and a “7.5% average return.” Are these guaranteed?
No. Any historical results are illustrative and not guarantees of future performance. Markets are risky; use risk management and testing.
5) Can I filter the Moonshots list?
Yes—pass parameters like min_grade, signal, and limit (as supported) to tailor to your audience and keep pages fast.
6) Do you provide SDKs or examples?
REST works with JavaScript and Python snippets above. Docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.
7) Pricing, limits, and enterprise SLAs?
Begin free and scale up. See API plans for rate limits and enterprise options.
Token Metrics API
Support and Resistance API: Auto-Calculate Smart Levels for Better Trades
Most traders still draw lines by hand in TradingView. The support and resistance API from Token Metrics auto-calculates clean support and resistance levels from one request, so your dashboard, bot, or alerts can react instantly. In minutes, you’ll call /v2/resistance-support, render actionable levels for any token, and wire them into stops, targets, or notifications. Start by grabbing your key on Get API Key, then Run Hello-TM and Clone a Template to ship a production-ready feature fast.
What You’ll Build in 2 Minutes
- A minimal script that fetches Support/Resistance via /v2/resistance-support for a symbol (e.g., BTC, SOL).
- A one-liner curl to smoke-test your key.
- A UI pattern to display nearest support, nearest resistance, level strength, and last updated time.
- Endpoints to add next: /v2/trading-signals (entries/exits), /v2/hourly-trading-signals (intraday updates), /v2/tm-grade (single-score context), /v2/quantmetrics (risk/return framing).
Why This Matters
Precision beats guesswork. Hand-drawn lines are subjective and slow. The support and resistance API standardizes levels across assets and timeframes, enabling deterministic stops and take-profits your users (and bots) can trust.
Production-ready by design. A simple REST shape, predictable latency, and clear semantics let you add levels to token pages, automate SL/TP alerts, and build rule-based execution with minimal glue code.
Where to Find
Need the Support and Resistance data? The cURL request for it is in the top right of the API Reference for quick access.
👉 Keep momentum: Get API Key • Run Hello-TM • Clone a Template
Live Demo & Templates
- SL/TP Alerts Bot (Telegram/Discord): Ping when price approaches or touches a level; include buffer %, link back to your app.
- Token Page Levels Panel (Dashboard): Show nearest support/resistance with strength badges; color the latest candle by zone.
- TradingView Overlay Companion: Use levels to annotate charts and label potential entries/exits driven by Trading Signals.
Kick off with our quickstarts—fork a bot or dashboard template, plug your key, and deploy. Confirm your environment by Running Hello-TM. When you’re scaling or need webhooks/limits, review API plans.
How It Works (Under the Hood)
The Support/Resistance endpoint analyzes recent price structure to produce discrete levels above and below current price, along with strength indicators you can use for priority and styling. Query /v2/resistance-support?symbol=<ASSET>&timeframe=<HORIZON> to receive arrays of level objects and timestamps.
Polling vs webhooks. For dashboards, short-TTL caching and batched fetches keep pages snappy. For bots and alerts, use queued jobs or webhooks (where applicable) to avoid noisy, bursty polling—especially around market opens and major events.
Production Checklist
- Rate limits: Respect plan caps; add client-side throttling.
- Retries/backoff: Exponential backoff with jitter for 429/5xx; log failures.
- Idempotency: Make alerting and order logic idempotent to prevent duplicates.
- Caching: Memory/Redis/KV with short TTLs; pre-warm top symbols.
- Batching: Fetch multiple assets per cycle; parallelize within rate limits.
- Threshold logic: Add %-of-price buffers (e.g., alert at 0.3–0.5% from level).
- Error catalog: Map common 4xx/5xx to actionable user guidance; keep request IDs.
- Observability: Track p95/p99; measure alert precision (touch vs approach).
- Security: Store API keys in a secrets manager; rotate regularly.
Use Cases & Patterns
- Bot Builder (Headless):
- Use nearest support for stop placement and nearest resistance for profit targets.
- Combine with /v2/trading-signals for entries/exits and size via Quantmetrics (volatility, drawdown).
- Use nearest support for stop placement and nearest resistance for profit targets.
- Dashboard Builder (Product):
- Add a Levels widget to token pages; badge strength (e.g., High/Med/Low) and show last touch time.
- Color the price region (below support, between levels, above resistance) for instant context.
- Add a Levels widget to token pages; badge strength (e.g., High/Med/Low) and show last touch time.
- Screener Maker (Lightweight Tools):
- “Close to level” sort: highlight tokens within X% of a strong level.
- Toggle alerts for approach vs breakout events.
- “Close to level” sort: highlight tokens within X% of a strong level.
- Risk Management:
- Create policy rules like “no new long if price is within 0.2% of strong resistance.”
- Export daily level snapshots for audit/compliance.
- Create policy rules like “no new long if price is within 0.2% of strong resistance.”
Next Steps
- Get API Key — generate a key and start free.
- Run Hello-TM — verify your first successful call.
- Clone a Template — deploy a levels panel or alerts bot today.
- Watch the demo: VIDEO_URL_HERE
- Compare plans: Scale confidently with API plans.
FAQs
1) What does the Support & Resistance API return?
A JSON payload with arrays of support and resistance levels for a symbol (and optional timeframe), each with a price and strength indicator, plus an update timestamp.
2) How timely are the levels? What are the latency/SLOs?
The endpoint targets predictable latency suitable for dashboards and alerts. Use short-TTL caching for UIs, and queued jobs or webhooks for alerting to smooth traffic.
3) How do I trigger alerts or trades from levels?
Common patterns: alert when price is within X% of a level, touches a level, or breaks beyond with confirmation. Always make downstream actions idempotent and respect rate limits.
4) Can I combine levels with other endpoints?
Yes—pair with /v2/trading-signals for timing, /v2/tm-grade for quality context, and /v2/quantmetrics for risk sizing. This yields a complete decide-plan-execute loop.
5) Which timeframe should I use?
Intraday bots prefer shorter horizons; swing/position dashboards use daily or higher-timeframe levels. Offer a timeframe toggle and cache results per setting.
6) Do you provide SDKs or examples?
Use the REST snippets above (JS/Python). The docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.
7) Pricing, limits, and enterprise SLAs?
Begin free and scale as you grow. See API plans for rate limits and enterprise SLA options.
Token Metrics API
Quantmetrics API: Measure Risk & Reward in One Call
Most traders see price—quants see probabilities. The Quantmetrics API turns raw performance into risk-adjusted stats like Sharpe, Sortino, volatility, drawdown, and CAGR so you can compare tokens objectively and build smarter bots and dashboards. In minutes, you’ll query /v2/quantmetrics, render a clear performance snapshot, and ship a feature that customers trust. Start by grabbing your key at Get API Key, Run Hello-TM to verify your first call, then Clone a Template to go live fast.
What You’ll Build in 2 Minutes
- A minimal script that fetches Quantmetrics for a token via /v2/quantmetrics (e.g., BTC, ETH, SOL).
- A smoke-test curl you can paste into your terminal.
- A UI pattern that displays Sharpe, Sortino, volatility, max drawdown, CAGR, and lookback window.
- Endpoints to add next: /v2/tm-grade (one-score signal), /v2/trading-signals / /v2/hourly-trading-signals (timing), /v2/resistance-support (risk placement), /v2/price-prediction (scenario planning).
Why This Matters
Risk-adjusted truth beats hype. Price alone hides tail risk and whipsaws. Quantmetrics compresses edge, risk, and consistency into metrics that travel across assets and timeframes—so you can rank universes, size positions, and communicate performance like a pro.
Built for dev speed. A clean REST schema, predictable latency, and easy auth mean you can plug Sharpe/Sortino into bots, dashboards, and screeners without maintaining your own analytics pipeline. Pair with caching and batching to serve fast pages at scale.
Where to Find
The Quant Metrics cURL request is located in the top right of the API Reference, allowing you to easily integrate it with your application.
👉 Keep momentum: Get API Key • Run Hello-TM • Clone a Template
Live Demo & Templates
- Risk Snapshot Widget (Dashboard): Show Sharpe, Sortino, volatility, and drawdown per token; color-code by thresholds.
- Allocator Screener: Rank tokens by Sharpe, filter by drawdown < X%, and surface a top-N list.
- Bot Sizer: Use Quantmetrics to scale position sizes (e.g., lower risk = larger size), combined with Trading Signals for entries/exits.
Kick off from quickstarts in the docs—fork a dashboard or screener template, plug your key, and deploy in minutes. Validate your environment with Run Hello-TM; when you need more throughput or webhooks, compare API plans.
How It Works (Under the Hood)
Quantmetrics computes risk-adjusted performance over a chosen lookback (e.g., 30d, 90d, 1y). You’ll receive a JSON snapshot with core statistics:
- Sharpe ratio: excess return per unit of total volatility.
- Sortino ratio: penalizes downside volatility more than upside.
- Volatility: standard deviation of returns over the window.
- Max drawdown: worst peak-to-trough decline.
- CAGR / performance snapshot: geometric growth rate and best/worst periods.
Call /v2/quantmetrics?symbol=<ASSET>&window=<LOOKBACK> to fetch the current snapshot. For dashboards spanning many tokens, batch symbols and apply short-TTL caching. If you generate alerts (e.g., “Sharpe crossed 1.5”), run a scheduled job and queue notifications to avoid bursty polling.
Production Checklist
- Rate limits: Understand your tier caps; add client-side throttling and queues.
- Retries & backoff: Exponential backoff with jitter; treat 429/5xx as transient.
- Idempotency: Prevent duplicate downstream actions on retried jobs.
- Caching: Memory/Redis/KV with short TTLs; pre-warm popular symbols and windows.
- Batching: Fetch multiple symbols per cycle; parallelize carefully within limits.
- Error catalog: Map 4xx/5xx to clear remediation; log request IDs for tracing.
- Observability: Track p95/p99 latency and error rates; alert on drift.
- Security: Store API keys in secrets managers; rotate regularly.
Use Cases & Patterns
- Bot Builder (Headless): Gate entries by Sharpe ≥ threshold and drawdown ≤ limit, then trigger with /v2/trading-signals; size by inverse volatility.
- Dashboard Builder (Product): Add a Quantmetrics panel to token pages; allow switching lookbacks (30d/90d/1y) and export CSV.
- Screener Maker (Lightweight Tools): Top-N by Sortino with filters for volatility and sector; add alert toggles when thresholds cross.
- Allocator/PM Tools: Blend CAGR, Sharpe, drawdown into a composite score to rank reallocations; show methodology for trust.
- Research/Reporting: Weekly digest of tokens with Sharpe ↑, drawdown ↓, and volatility ↓.
Next Steps
- Get API Key — start free and generate a key in seconds.
- Run Hello-TM — verify your first successful call.
- Clone a Template — deploy a screener or dashboard today.
- Watch the demo: VIDEO_URL_HERE
- Compare plans: Scale with API plans.
FAQs
1) What does the Quantmetrics API return?
A JSON snapshot of risk-adjusted metrics (e.g., Sharpe, Sortino, volatility, max drawdown, CAGR) for a symbol and lookback window—ideal for ranking, sizing, and dashboards.
2) How fresh are the stats? What about latency/SLOs?
Responses are engineered for predictable latency. For heavy UI usage, add short-TTL caching and batch requests; for alerts, use scheduled jobs or webhooks where available.
3) Can I use Quantmetrics to size positions in a live bot?
Yes—many quants size inversely to volatility or require Sharpe ≥ X to trade. Always backtest and paper-trade before going live; past results are illustrative, not guarantees.
4) Which lookback window should I choose?
Short windows (30–90d) adapt faster but are noisier; longer windows (6–12m) are steadier but slower to react. Offer users a toggle and cache each window.
5) Do you provide SDKs or examples?
REST is straightforward (JS/Python above). Docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.
6) Polling vs webhooks for quant alerts?
Dashboards usually use cached polling. For threshold alerts (e.g., Sharpe crosses 1.0), run scheduled jobs and queue notifications to keep usage smooth and idempotent.
7) Pricing, limits, and enterprise SLAs?
Begin free and scale up. See API plans for rate limits and enterprise SLA options.
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Token Metrics Media LLC is a regular publication of information, analysis, and commentary focused especially on blockchain technology and business, cryptocurrency, blockchain-based tokens, market trends, and trading strategies.
Token Metrics Media LLC does not provide individually tailored investment advice and does not take a subscriber’s or anyone’s personal circumstances into consideration when discussing investments; nor is Token Metrics Advisers LLC registered as an investment adviser or broker-dealer in any jurisdiction.
Information contained herein is not an offer or solicitation to buy, hold, or sell any security. The Token Metrics team has advised and invested in many blockchain companies. A complete list of their advisory roles and current holdings can be viewed here: https://tokenmetrics.com/disclosures.html/
Token Metrics Media LLC relies on information from various sources believed to be reliable, including clients and third parties, but cannot guarantee the accuracy and completeness of that information. Additionally, Token Metrics Media LLC does not provide tax advice, and investors are encouraged to consult with their personal tax advisors.
All investing involves risk, including the possible loss of money you invest, and past performance does not guarantee future performance. Ratings and price predictions are provided for informational and illustrative purposes, and may not reflect actual future performance.
