Real-time market sentiment your agent can call directly.
Six-dimension sentiment, trade signals, and curated news, delivered over a clean REST API and native MCP, so the agent reasoning about a trade reads the signal directly. Live across 300+ crypto assets today, with forex, commodities, and stocks next. Works with Claude, ChatGPT, Gemini, Grok, and any LLM out of the box.
// The problem
Market intelligence wasn't built for agents
The incumbents have sentiment. It just lives where an agent can't reach it: inside a terminal or a closed model, priced for the institution and built for a human watching a screen.
Locked inside a terminal
Legacy market intelligence is delivered to an analyst staring at a screen. Agentic systems don't watch screens. Terminals were built for a human at a desk; Guavy was built for the agent making the decision.
Raw data has no scored context
A price tells your agent nothing on its own. Is sentiment rising or falling? Is the crowd speculating or convinced? Guavy scores the mood across six dimensions, so the signal is structured, not noise.
No standard agent integration
Most providers have no MCP server, no llms.txt, and no concept of agent-to-API access, so you write glue code. Guavy is API-first and MCP-native from day one.
Guavy is the layer agents call
Six-dimension sentiment, scored news, and trade signals over REST and native MCP. Institutional sentiment, without the terminal. Your agent is live in minutes.
// Use cases
What builders are creating
From solo developers to institutional quant teams, here's how Guavy's API powers real agentic workflows.
Sentiment-triggered alert agent
An agent that polls sentiment history across a portfolio of assets and fires alerts or webhooks when sentiment crosses defined thresholds. No manual monitoring required.
Signal-driven autonomous trader
Feed Guavy's buy/sell/hold signals and backtest data into an LLM-powered trading agent. Let it reason about when to enter and exit positions using AI-validated trend data.
Daily market intelligence brief
An agent that pulls the AI market summary, top movers, and instrument-specific analysis each morning and composes a concise brief delivered to Slack, email, or a dashboard.
Market-aware LLM with live context
Inject live Guavy news briefs into your RAG pipeline so your LLM answers questions with up-to-the-minute market context, not stale training data.
AI-powered market data app backend
Build a mobile or web app that surfaces personalized asset recommendations, sentiment charts, and curated news, all powered by a single Guavy API key.
Quant fund data feed
Augment quantitative models with AI-generated sentiment and signal data across every asset you track. Backtest against 5+ years of historical trend data with structured JSON responses.
// Quickstart
Live in under 5 minutes
No SDKs to install. Standard REST with Bearer token auth. Works with any HTTP client.
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Get a free API key
Sign up at guavy.com. No credit card needed for the Sandbox tier. Your key is ready instantly.
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Start making API calls
Use standard REST endpoints from any HTTP client. For AI integrations, paste
https://guavy.com/llms.txtinto Claude, GPT, or any LLM, and it auto-discovers every endpoint. -
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Or call the REST API directly
Standard GET endpoints. JSON responses. Add your Bearer token to the Authorization header and you're calling live market data in seconds.
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Connect via MCP (optional)
For native agent tool-use, use Guavy's MCP server to give your agent first-class access to sentiment, signals, and news as callable tools.
# Get live Bitcoin sentiment for your agent import requests API_KEY = "YOUR_GUAVY_API_KEY" BASE = "https://guavy.com/api/v1" headers = { "Authorization": f"Bearer {API_KEY}" } # Fetch today's BTC sentiment r = requests.get( f"{BASE}/sentiment/get-sentiment-history/btc", headers=headers, params={"limit": 1} ) today = r.json()["sentiment"][0] print(f"BTC positive: {today['positive']}") print(f"BTC negative: {today['negative']}") # Get trade signal signal = requests.get( f"{BASE}/trades/get-current-action/btc/aggressive", headers=headers ).json() print(f"Signal: {signal['action']}") # → Signal: Buy
// Integrations
Works with every LLM and framework
Native llms.txt support means any LLM can understand and call the Guavy API without custom instructions.
// For AI agents
Your LLM already knows how to use Guavy
No prompt engineering. No custom function definitions. No glue code. Just point your agent at one URL.
The complete Guavy API specification (every endpoint, parameter, and response field) formatted for direct LLM consumption. Point your agent at this URL and it will understand exactly what to call and how, with no additional setup required.
https://guavy.com/llms.txt
as a document or paste the URL. Claude reads the spec and writes correct API calls immediately.
For agents that use tool-calling natively, Guavy's MCP server exposes sentiment, signals, and news as first-class callable tools. No REST wrappers needed.
MCP Setup GuidePrefer to build with the REST API directly? The complete docs cover every endpoint with example requests, response schemas, and code samples.
Read the docs// Pricing
Start free. Scale as you build.
No credit card needed for Sandbox. All prices in CAD.
- All 300+ coins (REST & MCP)
- Live sentiment & news
- 1 year historical data
- 3,000 tokens / month
- Personal use
- All 300+ coins
- Full sentiment & signals
- 3 years historical data
- 250,000 tokens / month
- Email support
- Personal use
- Everything in Quant
- 1,000,000 tokens / month
- Custom webhooks
- Priority support
- Full historical depth
- Personal use
// FAQ
Questions from AI builders
How do I connect Guavy to Claude or another LLM?
https://guavy.com/llms.txt. It contains the complete API spec in a format LLMs understand natively, so your agent knows every endpoint, parameter, and response format with no extra setup. For MCP-native integration, use the Guavy MCP server so your agent calls market data as first-class tools.Does Guavy support the Model Context Protocol (MCP)?
https://guavy.com/mcp, one of very few market-data APIs that integrates directly with agentic frameworks. Your agent discovers and calls every Guavy tool with no glue code. Works with Claude Desktop, Cursor, VS Code, Grok, Gemini CLI, and LangChain. Step-by-step setup guide What does "real-time" mean, and how fresh is the data?
get-market-summary and get-instrument-analysis endpoints are refreshed daily with AI-generated summaries of current conditions.Can I use Guavy data in a commercial product or SaaS app?
Which markets does Guavy cover, and how?
list-symbols endpoint to pull the full list programmatically.Is there a rate limit I need to worry about?
limit and skip) to batch requests efficiently.// Get started
Your agent is missing
live market sentiment
Free sandbox forever. No credit card required. Live data in minutes.