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Dune Query MCP

by olaxbt

DuneLink

Version Python

A modern bridge connecting Dune Analytics data to intelligent agents through Model Control Protocol (MCP).

Overview

DuneLink enables seamless integration of blockchain data analytics into your AI applications. By leveraging Dune Analytics' powerful query capabilities with the Model Control Protocol, this service allows LLMs and other AI systems to access on-chain data through simple, natural language interactions.

Core Capabilities

Data Retrieval Tools

Tool

Description

Use Case

get_latest_result

Retrieves pre-computed query results

Quick access to existing data

run_query

Executes a query on-demand

Real-time data analysis

Data Format

All data is returned in CSV format, providing:

  • Universal compatibility

  • Easy parsing by most data analysis tools

  • Human-readable output

Getting Started

System Requirements

Quick Setup

  1. Clone & Navigate

    git clone https://github.com/olaxbt/dune-query-mcp.git cd dunelink
  2. Environment Setup

    # Create virtual environment python -m venv .venv # Activate it source .venv/bin/activate # Linux/Mac # or .venv\Scripts\activate # Windows # Install dependencies pip install -r requirements.txt
  3. Configure API Access

    # Copy example config cp .env.example .env # Edit with your API key echo "DUNE_API_KEY=your_key_here" > .env

Usage

Running the Service

DuneLink offers two ways to run:

As MCP Service

python run.py

This starts the MCP service on default port 8000.

As Web Server

python flask_app.py

This provides access to the web interface and REST API endpoints.

Integrating with Applications

MCP Client Integration

from mcp.client import Client # Connect to DuneLink client = Client("http://localhost:8000") # Get latest results for a query csv_data = client.call("get_latest_result", query_id=1234567) # Execute a query query_results = client.call("run_query", query_id=1234567)

REST API

Endpoint

Method

Description

/dune/health

GET

Service health check

/dune/query/{query_id}/latest

GET

Retrieve latest results

/dune/query/{query_id}/execute

POST

Run a query

Example REST Call:

curl -X GET http://localhost:5000/dune/query/1234567/latest

Architecture

dunelink/ ├── app/ # Application core │ ├── __init__.py # Flask & MCP setup │ ├── routes/ # API endpoint definitions │ │ └── dune_routes/ # Dune Analytics routes │ │ └── templates/ # Web interface │ └── templates/ # Web interface ├── config/ # Configuration files ├── logs/ # Runtime logs ├── flask_app.py # Web server entry point ├── run.py # MCP server entry point └── requirements.txt # Dependencies

Advanced Configuration

Environment Variables

Variable

Purpose

Default

DUNE_API_KEY

Authentication for Dune API

None (Required)

PORT

Server port

8000

Performance Tuning

For high-volume query execution:

# Set a higher timeout for long-running queries export DUNE_QUERY_TIMEOUT=600 # 10 minutes in seconds

Troubleshooting

Common issues and solutions:

Problem

Solution

API Key errors

Ensure

.env

file exists with valid key

Timeout errors

Increase timeout for complex queries

CSV parsing issues

Check query returns proper tabular data

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository

  2. Create a feature branch: git checkout -b feature/amazing-feature

  3. Commit your changes: git commit -am 'Add some amazing feature'

  4. Push to the branch: git push origin feature/amazing-feature

  5. Open a Pull Request

License

This project is released under the MIT License. See LICENSE file for details.

Acknowledgments

-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A bridge that connects Dune Analytics blockchain data to AI applications through Model Control Protocol, allowing LLMs to access on-chain data via natural language interactions.

  1. Overview
    1. Core Capabilities
      1. Data Retrieval Tools
      2. Data Format
    2. Getting Started
      1. System Requirements
      2. Quick Setup
    3. Usage
      1. Running the Service
      2. Integrating with Applications
    4. Architecture
      1. Advanced Configuration
        1. Environment Variables
        2. Performance Tuning
      2. Troubleshooting
        1. Contributing
          1. License
            1. Acknowledgments

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