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kukapay

wormhole-metrics-mcp

by kukapay
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
get_cross_chain_activityB
Fetch cross-chain activity data from Wormholescan API and return as a pandas DataFrame.

Args:
    timeSpan: Time span for data (7d, 30d, 90d, 1y, all-time). Default: 7d
    by: Render results by notional or tx count. Default: notional
    app: Comma-separated list of apps. Default: all apps

Returns:
    String representation of a pandas DataFrame containing cross-chain activity data
get_money_flowB
Fetch transaction count and volume data from Wormholescan API for a specific period.

Args:
    timespan: Time span for data (1h, 1d, 1mo, 1y). Default: 1d
    from_date: From date in ISO 8601 format (e.g., 2024-01-01T15:04:05Z). Default: empty
    to_date: To date in ISO 8601 format (e.g., 2024-01-01T15:04:05Z). Default: empty
    appId: Application ID to filter results. Default: empty
    sourceChain: Source chain ID to filter results. Default: empty
    targetChain: Target chain ID to filter results. Default: empty

Returns:
    String representation of a pandas DataFrame containing transaction count and volume data
get_top_assets_by_volumeA
Fetch top assets by volume from Wormholescan API.

Args:
    timeSpan: Time span for data (7d, 15d, 30d). Default: 7d

Returns:
    String representation of a pandas DataFrame containing top assets by volume
get_top_chain_pairs_by_num_transfersB
Fetch top chain pairs by number of transfers from Wormholescan API.

Args:
    timeSpan: Time span for data (7d, 15d, 30d). Default: 7d

Returns:
    String representation of a pandas DataFrame containing top chain pairs by number of transfers
get_top_symbols_by_volumeB
Fetch top symbols by volume from Wormholescan API.

Args:
    timeSpan: Time span for data (7d, 15d, 30d). Default: 7d

Returns:
    String representation of a pandas DataFrame containing top symbols by volume
get_top100_corridorsB
Fetch top 100 token corridors by number of transactions from Wormholescan API.

Args:
    timeSpan: Time span for data (2d, 7d). Default: 2d

Returns:
    String representation of a pandas DataFrame containing top 100 corridors
get_kpi_listB
Fetch a list of KPIs for Wormhole from Wormholescan API.

Returns:
    String representation of a pandas DataFrame containing Wormhole KPIs

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
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TDQS

A3.6/5.0

Scored across 7 tools

Disambiguation4/5

Most tools have clearly distinct purposes focused on different Wormhole metrics (cross-chain activity, KPIs, money flow, corridors, assets, chain pairs, symbols). However, get_top_assets_by_volume and get_top_symbols_by_volume could potentially overlap in scope since symbols often represent assets, though their descriptions suggest different data dimensions.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with 'get_' prefix and descriptive names (e.g., get_cross_chain_activity, get_kpi_list). The naming is uniform throughout the set with no deviations in style or structure.

Tool Count5/5

7 tools is well-scoped for a metrics-focused MCP server. Each tool addresses a specific aspect of Wormhole analytics (activity, KPIs, flows, top items), and none appear redundant or unnecessary for the domain.

Completeness4/5

The toolset provides comprehensive coverage for fetching Wormhole metrics data across key dimensions (activity, flows, top items, KPIs). A minor gap exists in lacking tools for historical trend analysis or comparative metrics over time, but core data retrieval is well-covered.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources