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nipunbatra

VayuChat MCP

by nipunbatra
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

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

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{
  "tasks": {
    "list": {},
    "cancel": {},
    "requests": {
      "tools": {
        "call": {}
      },
      "prompts": {
        "get": {}
      },
      "resources": {
        "read": {}
      }
    }
  }
}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_tablesB

List all available tables/dataframes with their descriptions.

Returns: Summary of all available tables.

show_tableC

Display rows from a table.

Args: name: Table name (air_quality, funding, city_info) rows: Number of rows to show (default: 10) columns: Optional list of columns to display

Returns: Formatted table data.

describe_tableC

Get detailed statistics for a table.

Args: name: Table name

Returns: Statistical summary and column info.

query_tableB

Filter a table using pandas query syntax.

Args: name: Table name query: Pandas query (e.g., "city == 'Delhi' and PM2.5 > 200")

Returns: Filtered results.

compare_weekday_weekendC

Compare weekday vs weekend values for a metric.

Args: value_column: Column to compare (e.g., 'PM2.5', 'PM10') group_by: Optional grouping column (e.g., 'city') table: Table name (default: air_quality)

Returns: Comparison statistics.

compare_citiesC

Compare a metric across cities.

Args: value_column: Column to compare (e.g., 'PM2.5') cities: Optional list of cities to compare table: Table name (default: air_quality)

Returns: City comparison statistics.

analyze_correlationC

Analyze correlations between numeric columns.

Args: columns: Optional list of columns to analyze target: Optional target column to show correlations with table: Table name (default: air_quality)

Returns: Correlation analysis.

analyze_fundingC

Analyze air quality funding data.

Args: city: Optional city to filter by year: Optional year to filter by

Returns: Funding analysis.

get_city_profileB

Get comprehensive profile for a city including all available data.

Args: city: City name (Delhi, Bangalore, Mumbai, etc.)

Returns: City profile with air quality, funding, and metadata.

plot_comparisonC

Create a comparison chart.

Args: value_column: Column to plot (e.g., 'PM2.5') group_column: Grouping column (default: 'city') chart_type: 'bar', 'horizontal_bar', or 'box' table: Table name title: Optional title

Returns: Base64 encoded plot.

plot_time_seriesC

Create a time series plot.

Args: value_column: Column to plot group_by: Optional column for separate lines (e.g., 'city') table: Table name title: Optional title

Returns: Base64 encoded plot.

plot_weekday_weekendC

Create weekday vs weekend comparison chart.

Args: value_column: Column to compare group_by: Grouping column (default: 'city') table: Table name title: Optional title

Returns: Base64 encoded plot.

plot_funding_trendB

Plot funding trends over years by city.

Args: cities: Optional list of cities to include title: Optional title

Returns: Base64 encoded plot.

plot_hourly_patternC

Plot hourly patterns.

Args: value_column: Column to plot group_by: Optional grouping column table: Table name title: Optional title

Returns: Base64 encoded plot.

execute_codeC

Execute custom Python code for advanced analysis.

Available variables:

  • air_quality, funding, city_info: DataFrames

  • pd, np, plt: Libraries

Args: code: Python code to execute

Returns: Output from code execution.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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