Bankless Onchain MCP Server
MCP (Model Context Protocol) server for blockchain data interaction through the Bankless API.
Overview
The Bankless Onchain MCP Server provides a framework for interacting with on-chain data via the Bankless API. It implements the Model Context Protocol (MCP) to allow AI models to access blockchain state and event data in a structured way.
Features
The server provides the following onchain data operations:
Contract Operations
- Read Contract State (
read_contract): Read state from smart contracts on various blockchain networks.
- Get Proxy (
get_proxy): Retrieve proxy implementation contract addresses.
- Get ABI (
get_abi): Fetch the ABI (Application Binary Interface) for a contract.
- Get Source (
get_source): Retrieve the source code for a verified contract.
Event Operations
- Get Events (
get_events): Fetch event logs for a contract based on topics.
- Build Event Topic (
build_event_topic): Generate an event topic signature from event name and argument types.
Transaction Operations
- Get Transaction History (
get_transaction_history): Retrieve transaction history for a user address.
- Get Transaction Info (
get_transaction_info): Get detailed information about a specific transaction.
Tools
- read_contract
- get_proxy
- get_events
- build_event_topic
Installation
Usage
Environment Setup
Before using the server, set your Bankless API token. For details on how to obtain your Bankless API token, head to https://docs.bankless.com/bankless-api/other-services/onchain-mcp
Running the Server
The server can be run directly from the command line:
Usage with LLM Tools
This server implements the Model Context Protocol (MCP), which allows it to be used as a tool provider for compatible AI models. Here are some example calls for each tool:
read_contract
get_proxy
get_events
build_event_topic
Development
Building from Source
Debug Mode
Integration with AI Models
To integrate this server with AI applications that support MCP, add the following to your app's server configuration:
Error Handling
The server provides specific error types for different scenarios:
BanklessValidationError: Invalid input parameters
BanklessAuthenticationError: API token issues
BanklessResourceNotFoundError: Requested resource not found
BanklessRateLimitError: API rate limit exceeded
Prompting Tips
In order to guide an LLM model to use the Bankless Onchain MCP Server, the following prompts can be used:
Note: Code block was split into 2 parts due to size limits.
License
MIT
Bankless Onchain MCP Server
MCP (Model Context Protocol) server for blockchain data interaction through the Bankless API.
Overview
The Bankless Onchain MCP Server provides a framework for interacting with on-chain data via the Bankless API. It implements the Model Context Protocol (MCP) to allow AI models to access blockchain state and event data in a structured way.
Features
The server provides the following onchain data operations:
Contract Operations
- Read Contract State (
read_contract): Read state from smart contracts on various blockchain networks.
- Get Proxy (
get_proxy): Retrieve proxy implementation contract addresses.
- Get ABI (
get_abi): Fetch the ABI (Application Binary Interface) for a contract.
- Get Source (
get_source): Retrieve the source code for a verified contract.
Event Operations
- Get Events (
get_events): Fetch event logs for a contract based on topics.
- Build Event Topic (
build_event_topic): Generate an event topic signature from event name and argument types.
Transaction Operations
- Get Transaction History (
get_transaction_history): Retrieve transaction history for a user address.
- Get Transaction Info (
get_transaction_info): Get detailed information about a specific transaction.
Tools
- read_contract
- get_proxy
- get_events
- build_event_topic
Installation
Usage
Environment Setup
Before using the server, set your Bankless API token. For details on how to obtain your Bankless API token, head to https://docs.bankless.com/bankless-api/other-services/onchain-mcp
Running the Server
The server can be run directly from the command line:
Usage with LLM Tools
This server implements the Model Context Protocol (MCP), which allows it to be used as a tool provider for compatible AI models. Here are some example calls for each tool:
read_contract
get_proxy
get_events
build_event_topic
Development
Building from Source
Debug Mode
Integration with AI Models
To integrate this server with AI applications that support MCP, add the following to your app's server configuration:
Error Handling
The server provides specific error types for different scenarios:
BanklessValidationError: Invalid input parameters
BanklessAuthenticationError: API token issues
BanklessResourceNotFoundError: Requested resource not found
BanklessRateLimitError: API rate limit exceeded
Prompting Tips
In order to guide an LLM model to use the Bankless Onchain MCP Server, the following prompts can be used:
Note: Code block was split into 2 parts due to size limits.
License
MIT