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AI Revamp #987
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{ | ||
"graph-assistant": "Graph Assistant", | ||
"ai-introduction": "The Graph's AI", | ||
"subgraph-mcp": "Subgraph MCP", | ||
"token-api-mcp": "Token API MCP" | ||
} |
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import titles from './_meta-titles.json' | ||
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export default { | ||
'ai-introduction': titles['ai-introduction'], | ||
'graph-assistant': titles['graph-assistant'], | ||
'subgraph-mcp': titles['subgraph-mcp'], | ||
'token-api-mcp': titles['token-api-mcp'], | ||
} |
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--- | ||
title: The Graph's AI | ||
--- | ||
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Build with speed and scale faster with The Graph's AI. | ||
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## Using AI on The Graph | ||
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Instead of relying on static datasets or centralized APIs, you can now access live blockchain data through an **agentic** context using [Graph Assistant](/ai-suite/graph-assistant/introduction/), [Subgraph MCP](/ai-suite/subgraph-mcp/introduction/), and [Token API MCP](/ai-suite/token-api-mcp/introduction/). | ||
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### Why Use Onchain Data with AI? | ||
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Using onchain data with AI unlocks powerful new ways to interact with and understand blockchain ecosystems. | ||
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- **AI for Non-Technical End Users**: AI can turn complex onchain data into accessible insights. Assistants powered by AI enable you to explore and analyze blockchain data, without requiring any coding. | ||
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- **AI for Developers**: You can use AI to interact directly with The Graph's data through your agents or build AI-powered applications on top of it. This streamlines development and opens up more intuitive, dynamic use cases. | ||
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## AI for Non-Technical/End Users | ||
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[Graph Assistant](/ai-suite/graph-assistant/introduction/) is a powerful **agentic** application that empowers users to easily interact with blockchain data. Ask questions in simple, natural language and get rich, AI powered insights. Both technical developers and non-technical product teams can move faster, make smarter decisions, and gain a clearer understanding than ever before. | ||
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### Benefits of Using Graph Assistant | ||
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- **Natural language Input**: You don't need to write complex queries or sift through dashboards. Simply ask your question in plain English and get clear, structured results. | ||
- **Multi-source support**: Works across multiple Subgraphs and The Graph's APIs. The assistant automatically determines which data source to use, so you don't have to switch tools or manage endpoints. | ||
- **Schema-free access**: You don't need to understand the schema. You can refer to tokens, protocols, dates, or addresses using natural language. The assistant takes care of the rest. | ||
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### Conversational Querying with Graph Assistant | ||
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**Example queries:** | ||
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- "List the top-5 swaps by USD value in the last 24 hours." | ||
- "Give me the daily volume on Uniswap." | ||
- "List the 20 most recently registered .eth names." | ||
- "Whats the best liqudity pool to put my ETH into?" | ||
- "Total delegated stake in The Graph network?" | ||
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[Graph Assistant](/ai-suite/graph-assistant/introduction/) will eventually be a one-stop shop for interacting with The Graph. Right now, it's an agentic AI app that uses state-of-the-art AI techniques, LLMs, and MCPs to understand and answer your questions about [Subgraphs](/subgraphs/developing/subgraphs/) and [Token API](/token-api/quick-start/) data. | ||
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## AI for Developers | ||
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### Enable Natural Language Access to Onchain Data | ||
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[Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP) servers connect language models like Claude, Cline, and Cursor to blockchain data sources. They enable models to understand, query, and interact with structured onchain data using natural language. MCPs remove the need to write low-level queries or interact with APIs directly. | ||
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### Subgraph MCP | ||
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The [Subgraph MCP](/ai-suite/subgraph-mcp/introduction/) server connects models to Subgraphs on The Graph Network. It allows language models to explore Subgraph schemas, execute GraphQL queries, find relevant Subgraphs by keyword or contract, and surface usage metrics using natural language. | ||
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### Token API MCP | ||
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The [Token API MCP](/ai-suite/token-api-mcp/introduction/) MCP server enables models to access onchain token data. It supports querying token metadata, wallet balances, transfer history, and top token holders through simple prompts. | ||
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#### Benefits of Using Subgraph and Token API MCPs | ||
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- Query Subgraphs and token data using natural language | ||
- Access GraphQL schemas and token metadata without manual queries | ||
- Find Subgraphs by keyword or contract and check 30-day usage | ||
- Retrieve real-time data from The Graph and onchain token sources | ||
- Get wallet balances, transfer history, and top token holders |
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export default { | ||
'quick-start': '', | ||
introduction: '', | ||
'how-to-guide': '', | ||
faq: '', | ||
} |
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--- | ||
title: Graph Assistant FAQ | ||
sidebarTitle: 'FAQ' | ||
--- | ||
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This page summarizes some of the most common questions for developers using Graph Assistant. | ||
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1. What is The Graph Assistant? | ||
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The Graph Assistant is an AI-powered chat interface that lets you query blockchain data in plain English. Under the hood, it translates your questions into GraphQL calls against subgraphs and the Token API, then returns results as a table—no coding required. | ||
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2. What is an agentic application? | ||
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An agentic application combines AI-driven reasoning with external data sources or APIs to take autonomous actions on your behalf. In this case, Graph Assistant acts as an “agent” that interprets your natural-language prompts, builds and dispatches GraphQL queries, and formats the results so that you don't need to write or manage queries yourself. | ||
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3. Which networks and data does Graph Assistant support? | ||
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The assistant has access to Subgraphs across 100+ chains. If a Subgraph is published to The Graph Network and is being indexed, the assistant can automatically route queries to it. The assistant also has access to the Token API on Ethereum Mainnet, BSC, Unichain, Arbitrum-One, Optimism, and Polygon. | ||
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4. Is there a usage limit or quota? | ||
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10 questions per hour. | ||
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5. What if the assistant can't interpret my question? | ||
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When the assistant fails to parse your intent (for example, ambiguous token name, missing context, or an unsupported request), it will prompt you for clarification. For instance, it might ask, “Did you mean XYZ on Ethereum or XYZ on Arbitrum?” or “Please specify a date range for this query.” If you continue to see parsing errors, check that you're using correct token symbols or specifying networks and time frames clearly. |
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website/src/pages/en/ai-suite/graph-assistant/how-to-guide.mdx
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--- | ||
title: How To Use The Graph Assistant | ||
sidebarTitle: 'How-to Guide' | ||
--- | ||
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## Overview | ||
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You type a natural language question into the chat interface, such as: | ||
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```yaml | ||
'On Uniswap, return the top-10 pools by total value locked in USD.' | ||
``` | ||
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> [!IMPORTANT] All users can process 10 free queries per user per hour | ||
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### Behind the Scenes | ||
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The assistant: | ||
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1. Interprets your intent | ||
2. Maps it to the correct Subgraphs or Token API endpoint | ||
3. Executes optimized queries | ||
4. Returns results as a clean, readable table. | ||
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You don't need to write queries or understand a Subgraph's schema, you simply ask. | ||
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### Example Use Cases | ||
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**Protocol Analytics** | ||
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- “Compare daily active users on Aave vs. Compound in May 2025.” | ||
- “Show me the total value locked (TVL) for XYZDAO over the last quarter.” | ||
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**Token Insights** | ||
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- “What are the top 10 tokens by market cap on Ethereum right now?” | ||
- “How many XYZ did I receive between May 1 and May 15?” | ||
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**Historical Data Retrieval** | ||
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- “Fetch the token price history of XYZ for the last six months.” | ||
- “What was the average gas price on Ethereum during April?” | ||
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**Portfolio Monitoring** | ||
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- “List my wallet’s current token balances and their USD equivalents.” | ||
- “Calculate profit/loss on XYZ since xyz date.” | ||
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**Cross-Chain Comparison** | ||
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- “Show me the 7-day trading volume of XYZ on Ethereum vs. Polygon.” | ||
- “How many XYZ swaps occurred on Arbitrum yesterday?” | ||
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To get started follow the [quickstart](/ai-suite/graph-assistant/quick-start/) and explore it's capabilities. |
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website/src/pages/en/ai-suite/graph-assistant/introduction.mdx
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--- | ||
title: Introduction | ||
--- | ||
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[Graph Assistant](https://graph-assistant.vercel.app/) gives instant, code-free access to blockchain data, transforming natural language into precise, AI-powered queries without the need to code. | ||
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## Overview | ||
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[Graph Assistant](https://graph-assistant.vercel.app/) is an advanced, [agentic](/en/ai-suite/graph-assistant/faq/) easy-to-use chat interface for querying blockchain data using natural language. Unlike a basic chatbot, Graph Assistant can understand your intent, build complex queries, and execute them automatically. This gives you rich, AI-powered insights from onchain data without writing any code. | ||
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- **Automatically** interprets user intent, generates precise queries, executes them via The Graph's Subgraphs and Token API, and presents structured, AI-powered answers without requiring any code. | ||
- **Removes** the technical complexity found in traditional dashboards or chatbots. It provides composable insights directly from indexed Subgraphs and Token datasets. | ||
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## Core Features | ||
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| Feature | Description | | ||
| --- | --- | | ||
| **Friendly Interface** | Conversational access to blockchain data via natural language. You simply ask questions, the assistant fetches the answer, and renders it as a table | | ||
| **Backed by Subgraphs** | Uses subgraphs to index protocol-specific data like transactions, events, and protocol metrics | | ||
| **Backed by Token API** | Uses Token API for token-level information like balances, transfers, and metadata. | | ||
| **No Setup Required** | No need to configure data sources or write queries. | | ||
| **Automatic Query Building** | The assistant performs complex queries such as fetching historical token volumes, protocol analytics, or cross-chain data and handles filtering, pagination, and joins across Subgraphs automatically. | |
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website/src/pages/en/ai-suite/graph-assistant/quick-start.mdx
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--- | ||
title: Quick Start | ||
--- | ||
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This guide provides step-by-step instructions for getting started with Graph Assistant quickly. | ||
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## Step-by Step | ||
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### Step 1. Create an Account | ||
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Go to: [Graph AI](https://graph-assistant.vercel.app/) | ||
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- Click Sign Up (or Log In if you already have an account). | ||
- Use your GitHub or email credentials. | ||
- No additional setup is required | ||
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### Step 2. Open the Assistant Chat | ||
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After logging in: | ||
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- You'll see the assistant interface. | ||
- At the bottom of the page, you will find a chat input bar. This is where you will interact with the assistant. | ||
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### Step 3: Ask Your First Question | ||
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> [!IMPORTANT] All users can process 10 free queries per user per hour | ||
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In the input bar, type a natural-language query (everyday language). | ||
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Example: | ||
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```yaml | ||
Show me the 24-hour trading volume of XYZ token on Ethereum | ||
``` | ||
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The assistant will: | ||
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- Digest your question | ||
- Fetch onchain data using Subgraphs or the Token API | ||
- Return a clean, formatted response with the data you need |
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export default { | ||
introduction: '', | ||
claude: '', | ||
cline: '', | ||
cursor: '', | ||
|
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website/src/pages/en/ai-suite/subgraph-mcp/introduction.mdx
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--- | ||
title: Subgraph MCP Introduction | ||
sidebarTitle: 'Introduction' | ||
--- | ||
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The Subgraph [Model Context Protocol](https://modelcontextprotocol.io/introduction) MCP server connects large language models like Claude, Cline, and Cursor directly to Subgraphs on The Graph Network. This integration enables you to explore Subgraph data, run queries, and find relevant deployments using natural language prompts. | ||
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## What You Can Do | ||
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- Access GraphQL schemas for any Subgraph on The Graph Network | ||
- Run GraphQL queries on any Subgraph deployment | ||
- Discover top Subgraph deployments by keyword or contract address | ||
- Retrieve 30-day query volumes for Subgraph deployments | ||
- Ask questions about Subgraph data without writing GraphQL manually | ||
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The Subgraph MCP server allows smooth integration with [Claude](/ai-suite/subgraph-mcp/claude/), [Cline](/ai-suite/subgraph-mcp/cline/), or [Cursor](/ai-suite/subgraph-mcp/cursor/), making blockchain data queries with The Graph Network a conversational experience. |
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export default { | ||
introduction: '', | ||
claude: '', | ||
cline: '', | ||
cursor: '', | ||
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website/src/pages/en/ai-suite/token-api-mcp/introduction.mdx
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--- | ||
title: Token API MCP Introduction | ||
sidebarTitle: 'Introduction' | ||
--- | ||
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The Token [Model Context Protocol](https://modelcontextprotocol.io/introduction) MCP server connects Claude, Cline, and Cursor to onchain token data using natural language. This integration allows each model to fetch token metadata, track balances, analyze transfers, and surface holder insights without manual queries. | ||
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## What You Can Do | ||
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- Retrieve token metadata including name, symbol, decimals, total supply, and contract address | ||
- Get token balances for any wallet address holding a supported ERC-20 token | ||
- Fetch token transfer activity including sender, receiver, amount, and timestamp | ||
- Identify top holders and analyze token distribution | ||
- Ask natural language questions about token data without writing smart contract calls | ||
- Access historical transfer data to analyze token movement over time | ||
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The Token MCP server provides [Claude](/ai-suite/token-api-mcp/claude/), [Cline](/ai-suite/token-api-mcp/cline/), and [Cursor](/ai-suite/token-api-mcp/cursor/) with direct, conversational access to onchain token data. |
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