get_cross_chain_activityLABSCO SUMMARY
Bridge flow, read as a table.
Which chains are sending value to which, in what asset and at what size, over a window you choose — the questions a bridge dashboard answers, without opening one.
What it is
A Python server over Wormhole's metrics that returns Markdown tables. It pivots volume between source and destination chains over a window you pick, reports transaction count and volume for a route, and ranks assets by volume, with further tools for chain pairs, symbols, token corridors and headline KPIs.
What you get
- get_cross_chain_activity returns a pivot table of volume between source and destination chains over 7d, 30d, 90d, 1y or all-time, measured by notional or transaction count and optionally filtered to named apps
- get_money_flow returns transaction count and volume for a route
- get_top_assets_by_volume ranks the assets moving the most value
- Further tools cover chain pairs, symbols, token corridors and protocol KPIs
- Everything arrives as a Markdown table, so a bridge question is answerable without a charting tool
Requirements
Python 3.10 or higher with uv; install it into Claude Desktop with uv run mcp install main.py. No account and no key.
Setup effort
Build from source — git clone https://github.com/kukapay/wormhole-metrics-mcp.git
USE CASES
01
Seeing which corridors are busy
A pivot of volume between source and destination chains, by notional or by transaction count.
02
Sizing one route
Transaction count and volume for the specific pair you care about.
03
Finding what is actually being bridged
Assets ranked by volume, which is usually a shorter list than people expect.
04
Comparing a week against a year
The same pivot takes 7d, 30d, 90d, 1y or all-time, so a spike can be checked against the baseline in two calls.
7 tools
Listed in project docs. Your client may show a different list.
get_money_flowget_top_assets_by_volumeget_top_chain_pairs_by_num_transfersget_top_symbols_by_volumeget_top100_corridorsget_kpi_listBEFORE YOU INSTALL
What to know first
Tools you get
7 tools named in the project's documentation.
Requires
- Python 3.10 or later
- uv on PATH
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
git clone https://github.com/kukapay/wormhole-metrics-mcp.git
cd wormhole-metrics-mcp
uv sync
uv run mcp install main.py --name "Wormhole Metrics"MCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"Wormhole Metrics": {
"command": "uv",
"args": [
"--directory",
"<YOUR_PATH_TO_WORMHOLE_METRICS_MCP>",
"run",
"main.py"
]
}
}
}
