MCP Connector

Access Ergo Blockchain Data for AI Analysis

Ergo Blockchain MCP Server provides AI assistants with direct access to Ergo blockchain data through a standardized interface.

Works with githubdockeropen webui

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90
Spark score
out of 100
Updated 5 months ago
Version 1.0.0
Models
universal

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Why it matters

Integrate AI assistants with the Ergo blockchain, providing direct access to on-chain data for exploration, analysis, and visualization.

Outcomes

What it gets done

01

Retrieve blocks, transactions, and network statistics.

02

Analyze address balances, transaction history, and token holder distribution.

03

Generate interactive network visualizations for entity analysis.

04

Perform advanced analytics on blockchain patterns and token metrics.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-ergo-blockchain-mcp | bash

Capabilities

Tools your agent gets

openwebui_entity_tool

Returns a text summary of detected entities for an address

openwebui_viz_tool

Displays an interactive D3.js network visualization for address clustering

Overview

Ergo Blockchain MCP Server

The description now focuses on the server providing direct access to Ergo blockchain data for AI assistants.

Installation

From Source Code

git clone https://github.com/ergo-mcp/ergo-explorer-mcp.git
cd ergo-explorer-mcp
pip install -r requirements.txt
python -m ergo_explorer.server

Docker

docker build -t ergo-explorer-mcp .
docker run -d -p 8000:8000 \
  -e ERGO_EXPLORER_API="https://api.ergoplatform.com/api/v1" \
  -e ERGO_NODE_API="http://your-node-address:9053" \
  -e ERGO_NODE_API_KEY="your-api-key" \
  --name ergo-mcp ergo-explorer-mcp

Available Tools

| Tool |
|------| Description |
| openwebui_entity_tool | Returns a text summary of detected entities for an address |
| openwebui_viz_tool | Displays an interactive D3.js network visualization for address clustering |

Capabilities

  • Blockchain Exploration: Retrieve blocks, transactions, and network statistics
  • Address Analysis: Query balances, transaction history, and perform forensic analysis
  • Token Analytics: View token information, holder distribution, track historical ownership, and collection data
  • Ecosystem Integration: Access EIP information, oracle pool data, and address book
  • Advanced Analytics: Analyze blockchain patterns, token metrics, and transaction flows
  • Entity Identification: Discover related addresses using advanced address clustering algorithms
  • Interactive Visualizations: Generate and interact with network visualizations for entity analysis
  • Response Standardization: Support for two formats (JSON/Markdown) with consistent structure
  • Token Estimation: Built-in token counting for AI context window optimization
  • Historical Token Holder Tracking: Complete token history with block height tracking

Environment Variables

Required

  • ERGO_EXPLORER_API - URL for Ergo Explorer API

Optional

  • ERGO_NODE_API - URL for Ergo Node API (optional for advanced functions)
  • ERGO_NODE_API_KEY - API key for Ergo Node API (optional)

Usage Examples

Check blockchain status and network statistics
Analyze address balances and transaction history
Identify entities related to an address using clustering algorithms
Track historical token holder distribution
Monitor token transfers and ownership changes

Notes

The server includes comprehensive entity identification capabilities through address clustering algorithms, integration with Open WebUI for enhanced visualization, and built-in token estimation for AI context optimization. All responses follow a standardized format with metadata including execution time, result size, and token estimates.

Source README

An MCP server that provides AI assistants with direct access to Ergo blockchain data through a standardized interface, enabling blockchain exploration, address analysis, token information retrieval, and advanced analytics.

Installation

From Source Code

git clone https://github.com/ergo-mcp/ergo-explorer-mcp.git
cd ergo-explorer-mcp
pip install -r requirements.txt
python -m ergo_explorer.server

Docker

docker build -t ergo-explorer-mcp .
docker run -d -p 8000:8000 \
  -e ERGO_EXPLORER_API="https://api.ergoplatform.com/api/v1" \
  -e ERGO_NODE_API="http://your-node-address:9053" \
  -e ERGO_NODE_API_KEY="your-api-key" \
  --name ergo-mcp ergo-explorer-mcp

Available Tools

Tool Description
openwebui_entity_tool Returns a text summary of detected entities for an address
openwebui_viz_tool Displays an interactive D3.js network visualization for address clustering

Capabilities

  • Blockchain Exploration: Retrieve blocks, transactions, and network statistics
  • Address Analysis: Query balances, transaction history, and perform forensic analysis
  • Token Analytics: View token information, holder distribution, track historical ownership, and collection data
  • Ecosystem Integration: Access EIP information, oracle pool data, and address book
  • Advanced Analytics: Analyze blockchain patterns, token metrics, and transaction flows
  • Entity Identification: Discover related addresses using advanced address clustering algorithms
  • Interactive Visualizations: Generate and interact with network visualizations for entity analysis
  • Response Standardization: Support for two formats (JSON/Markdown) with consistent structure
  • Token Estimation: Built-in token counting for AI context window optimization
  • Historical Token Holder Tracking: Complete token history with block height tracking

Environment Variables

Required

  • ERGO_EXPLORER_API - URL for Ergo Explorer API

Optional

  • ERGO_NODE_API - URL for Ergo Node API (optional for advanced functions)
  • ERGO_NODE_API_KEY - API key for Ergo Node API (optional)

Usage Examples

Check blockchain status and network statistics
Analyze address balances and transaction history
Identify entities related to an address using clustering algorithms
Track historical token holder distribution
Monitor token transfers and ownership changes

Notes

The server includes comprehensive entity identification capabilities through address clustering algorithms, integration with Open WebUI for enhanced visualization, and built-in token estimation for AI context optimization. All responses follow a standardized format with metadata including execution time, result size, and token estimates.

FAQ

Common questions

Discussion

Questions & comments · 0

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