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MCP Server

MCP Server

Local
github.com/zaki9501Finance0Updated 80w ago
Repository

About MCP Server

A Node.js REST API for developers working with the Monad Testnet. It provides endpoints for blockchain queries, block analysis, contract data access, and chained operations.

Key features

  1. 01Express.js REST API
  2. 02Blockchain interaction via Web3.js
  3. 03Balance queries and transactions
  4. 04Block analysis and contract data access
  5. 05Swagger API documentation
  6. 06Docker support

Use cases

  1. 01Check the latest Monad Testnet block
  2. 02Analyze one or more blocks
  3. 03Read or write contract data

MCP support

The input describes a REST API service but does not specify how it relates to the MCP protocol.

#mcp-server#blockchain#nodejs

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "pikimon": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "build"
      ]
    }
  }
}
Run commanddocker run -i --rm build

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocibuild

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Server

A Node.js server for interacting with the Monad Testnet blockchain network. This server provides a REST API interface for common blockchain operations.

Features

  • Express.js REST API
  • Web3.js integration for blockchain interaction
  • Environment variable configuration
  • Basic blockchain operations (get balance, send transactions, etc.)
  • Security middleware (helmet, cors)
  • Swagger API documentation
  • Docker support

Prerequisites

  • Node.js (v16 or higher) OR Docker
  • npm (v8 or higher) if not using Docker
  • Access to a Monad Testnet node

Installation

Standard Installation

  1. Clone the repository:

    git clone <repository-url>
cd mcp-server

  2. Install dependencies:

    npm install

  3. Create environment file:

    cp .env.example .env

  4. Configure your environment variables in .env:

    • Set MONAD_RPC_URL to your Monad Testnet node URL
    • Set PORT if you want to use a different port
    • Add PRIVATE_KEY if needed for signing transactions
Docker Installation

  1. Clone the repository:

    git clone <repository-url>
cd mcp-server

  2. Create and configure environment file:

    cp .env.example .env
# Edit .env with your configuration

  3. Build the Docker image:

    docker build -t mcp-server .

  4. Run the container:

    docker run -d \
  --name mcp-server \
  -p 3000:3000 \
  --env-file .env \
  -v $(pwd)/logs:/app/logs \
  mcp-server

Usage

Standard Usage

Start the development server:

npm run dev

Start the production server:

npm start
Docker Usage

Start the container:

docker start mcp-server

Stop the container:

docker stop mcp-server

View logs:

docker logs mcp-server

API Documentation

The API documentation is available at /api-docs when the server is running. Visit:

http://localhost:3000/api-docs

API Endpoints

  • GET /health - Check server health
  • GET /blockchain/latest-block - Get current block number
  • GET /blockchain/analyze-block/:blockNumber - Get block analysis
  • POST /blockchain/store-data - Store data in contract
  • GET /blockchain/get-data - Get stored data
  • POST /actions/execute-chain - Execute chain of operations
  • GET /actions/parallel-block-analysis - Analyze multiple blocks

Environment Variables

VariableDescriptionDefault
PORTServer port3000
NODE_ENVEnvironment modedevelopment
MONAD_RPC_URLMonad Testnet RPC URLhttp://localhost:8545
CONTRACT_ADDRESSSmart contract address-
CONTRACT_ABISmart contract ABI-
LOG_LEVELLogging levelinfo

Docker Volumes

The container uses the following volume:

  • /app/logs: Contains application logs (combined.log and error.log)

License

ISC

Comments

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New to MCP?

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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.