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tron-event-mcp

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tron-event-mcp

TRON blockchain event data query MCP Server — let AI assistants analyze on-chain data directly.

Works with event-plugin: event-plugin writes TRON on-chain events into MongoDB in real time, and this project exposes that data to AI assistants (Claude, Cursor, etc.) via the Model Context Protocol (MCP), enabling natural-language-driven on-chain data analysis.

Data Source

event-plugin listens to a Java-tron node and writes the following 7 event types into MongoDB:

Collection

Description

Unique Index

block

Block event, triggered for every new block

blockNumber

transaction

Transaction event, triggered for every packaged transaction

transactionId

contractevent

Contract event, triggered when a smart contract emits an event (ABI-decoded)

uniqueId

contractlog

Contract raw log, not ABI-decoded (hex data)

uniqueId

solidity

Solidity trigger, fired when a block is finalized

latestSolidifiedBlockNumber

solidityevent

Solidified contract event, same structure as contractevent

uniqueId

soliditylog

Solidified contract raw log, same structure as contractlog

uniqueId

Related MCP server: mcp-server-tron

Available Tools

Metadata

Tool

Description

describe_schema

Return field descriptions, index info, and business meaning for all collections

get_collection_stats

Return document count and earliest/latest timestamps per collection

Query

Tool

Description

search_contract_activity

Query events/logs for a specific contract, with event name and time range filters

query_events

General-purpose query with arbitrary filters and field projection

count_events

Quickly count documents matching given criteria

get_block

Look up a block by height

get_transaction

Look up a transaction by hash

Aggregation & Analytics

Tool

Description

aggregate_field

Compute sum / avg / min / max on a specified field

group_by_field

Group-by aggregation for address rankings, event distribution, etc.

aggregate_by_time

Time-series aggregation (hour / day / week) with optional sum field

get_top_contracts

Leaderboard of most active contracts in a time range

Cross-Collection

Tool

Description

get_transaction_full

Full transaction view: details + associated contract events

get_address_profile

Address activity profile across sender, receiver, and contract caller roles

Distribution Analysis

Tool

Description

histogram

Numeric field bucketing with auto or manual boundaries

percentiles

Compute percentiles (P50 / P90 / P95 / P99, etc.)

Recommended Indexes

event-plugin itself only creates unique indexes (for data deduplication/upsert). To get optimal query performance with this MCP Server's analytics tools, add the following indexes to MongoDB:

// contractevent (highest query volume)
db.contractevent.createIndex({ contractAddress: 1, eventName: 1, timeStamp: -1 });
db.contractevent.createIndex({ contractAddress: 1, timeStamp: -1 });
db.contractevent.createIndex({ timeStamp: -1 });

// solidityevent
db.solidityevent.createIndex({ contractAddress: 1, eventName: 1, timeStamp: -1 });
db.solidityevent.createIndex({ contractAddress: 1, timeStamp: -1 });
db.solidityevent.createIndex({ timeStamp: -1 });

// transaction
db.transaction.createIndex({ timeStamp: -1 });
db.transaction.createIndex({ result: 1 });

// block
db.block.createIndex({ timeStamp: -1 });

// contractlog / soliditylog
db.contractlog.createIndex({ contractAddress: 1, timeStamp: -1 });
db.soliditylog.createIndex({ contractAddress: 1, timeStamp: -1 });

The create_index.js file in the project root contains the complete index creation script (unique + analytics indexes). Run it directly:

mongosh mongodb://host:27017/tron create_index.js

Quick Start

Prerequisites

  • Python >= 3.11

  • MongoDB >= 7.0 (the percentiles tool uses the $percentile aggregation operator, which requires 7.0+; all other tools work with 5.0+)

Installation

cd tron-event-mcp
make setup

Configuration

Edit the .env file (make setup copies it from .env.example automatically):

# MongoDB connection (strongly recommended to use a read-only user)
MONGO_URI=mongodb://readonly_user:password@host:27017/dbname?authSource=admin
MONGO_DB=tron

# Maximum documents per query (prevents fetching massive datasets)
MAX_RESULT_LIMIT=500

# Query timeout in milliseconds
QUERY_TIMEOUT_MS=10000

Running

# stdio mode (for local clients like Claude Code, Cursor, etc.)
make run

# SSE mode (for remote access)
make run-sse

Integration with Claude Code

Add the following to your Claude Code MCP configuration:

{
  "mcpServers": {
    "tron-events": {
      "command": "/path/to/tron-event-mcp/.venv/bin/python",
      "args": ["-m", "tron_event_mcp"]
    }
  }
}

Integration with Cursor

In Cursor Settings > MCP, add the same configuration as above.

Usage Examples

Once connected, you can ask questions in natural language:

  • "What are the most active contracts in the last 24 hours?"

  • "Show me the hourly USDT Transfer event volume trend"

  • "Analyze the on-chain activity of address TXxx..."

  • "What does the energy consumption distribution look like for transactions?"

  • "Show me the full details of transaction abc123..."

The AI assistant will automatically select the right combination of tools to answer.

Project Structure

tron-event-mcp/
├── src/tron_event_mcp/
│   ├── server.py            # MCP Server entry point; registers all tools and resources
│   ├── config.py            # Configuration management (env vars / .env)
│   ├── db/                  # MongoDB connection and query layer
│   ├── tools/
│   │   ├── schema.py        # describe_schema, get_collection_stats
│   │   ├── query.py         # get_recent_events, get_block, get_transaction, query_events
│   │   ├── analytics.py     # search_contract_activity, aggregate_field, group_by_field, etc.
│   │   ├── cross_collection.py  # get_transaction_full, get_address_profile
│   │   └── distribution.py  # histogram, percentiles
│   └── resources/           # MCP Resources (documentation resources)
├── tests/
├── pyproject.toml
├── Makefile
└── .env.example

Security Notes

  • Use a read-only MongoDB user — this tool only performs queries, no write access needed

  • Query filters forbid $where, $function, $accumulator and other code-execution operators

  • MAX_RESULT_LIMIT caps documents per request, protecting database performance

  • QUERY_TIMEOUT_MS enforces query timeout, preventing slow queries from blocking

License

MIT

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