Chainfetch MCP Server
The ChainFETCH MCP server provides API access to the Ethereum blockchain smart platform, integrating AI semantic search, real-time block streaming, and multi-modal query functions, supporting comprehensive analysis of addresses, transactions, blocks, tokens, and smart contracts.
rating : 2 points
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What is ChainFETCH MCP Server?
ChainFETCH MCP Server is a bridge server that connects AI assistants with Ethereum blockchain data. Through the Model Context Protocol, it allows you to query blockchain data using natural language without writing complex code or understanding technical details. The server integrates advanced AI technologies, including semantic search, intelligent analysis, and real-time data processing.How to use ChainFETCH MCP Server?
The usage process is very simple: 1) Obtain an API key. 2) Configure the MCP server. 3) Ask questions in natural language through a supported AI assistant (such as Claude). You can directly ask questions like 'Show recent large transactions' or 'Find addresses holding a large amount of ETH', and the server will automatically handle complex blockchain queries.Use Cases
Suitable for blockchain researchers, investors, developers, and any users interested in the Ethereum ecosystem. It can be used for monitoring large transactions, analyzing address behavior, researching smart contracts, tracking token flows, and conducting market research and due diligence.Main Features
Real-time Block Streaming
Process the latest Ethereum blocks every 12 seconds to ensure data real-time performance
AI Semantic Search
Use the Qwen3 embedding model for vector similarity search to understand query intentions
LLM Intelligent Query
The LLaMA 3.2 model automatically selects the best query parameters to optimize search results
Multi-modal Search
Supports three modes: semantic search, LLM natural language query, and structured JSON filtering
Comprehensive Data Coverage
Covers all Ethereum data types such as addresses, transactions, blocks, tokens, and smart contracts
AI Intelligent Summaries
Automatically generate AI analysis summaries of addresses, transactions, and contracts to quickly understand complex data
Advantages
No programming knowledge is required. You can query blockchain data using natural language
Real-time data processing, with timely information updates
AI intelligent analysis, automatically optimizing query parameters
Supports multiple search modes to meet different needs
Rich parameter filtering provides precise data screening
Limitations
Requires an API key and network connection
Limited support for very old historical data
Complex queries may take a long time to process
The free version may have query limit
How to Use
Obtain an API Key
Visit the chainfetch.app website to register an account and obtain an API access token
Install the Server
Globally install the ChainFETCH MCP server via NPM
Configure the AI Assistant
Configure the MCP server connection in a supported AI assistant such as Claude Desktop
Start Querying
Directly ask questions in natural language in the AI assistant interface, and the server will automatically handle them
Usage Examples
Whale Address Monitoring
Monitor the activities of addresses holding a large amount of ETH to detect large fund flows in a timely manner
Suspicious Transaction Analysis
Identify transaction patterns that may involve fraud or anomalies
Smart Contract Research
Analyze the features and activity patterns of newly deployed smart contracts
Token Flow Tracking
Track the flow of specific tokens between large addresses
Frequently Asked Questions
Do I need a blockchain technology background to use it?
How real-time is the data update?
Which AI assistants are supported?
Are there any restrictions on querying historical data?
How can I obtain an API key?
Related Resources
ChainFETCH Official Website
Obtain API keys and learn about the latest features
API Documentation
Detailed technical API documentation and parameter descriptions
GitHub Code Repository
Open-source code and issue feedback
MCP Protocol Description
Understand the technical details of the Model Context Protocol

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