Carbon Arc

Financeby Carbon Arc Corporation

Launched Mar 11, 2026 on ChatGPT

The Carbon Arc MCP Server is a business intelligence platform that converts natural language questions into insights for decision-making by providing access to private data.

Core Functions:

1. Ask questions like "Show me Walmart's 2024 card spend" and get structured data tables 2. Search for companies, locations, and metrics by name based on available data 3. Analyze trends across different time periods and geographic regions 4. Explore relationships between entities and available data

6ChatGPT Tools

Carbon Arc CorporationDeveloper

FinanceCategory

Available Tools

Framework to Insight

framework_to_insight

Full Description

Convert structured analytical frameworks into insights.

This tool takes a pre-defined analytical framework (structured query parameters) and executes it to generate insights. Useful when you have specific query parameters rather than natural language questions.

This provides more control than natural language queries and is ideal for programmatic access or when you know exactly what data structure you need.

Parameters (4 required, 1 optional)

Required

entitiesarray

List of entities to include in the framework

filters

Filters to apply to the framework

insight

Insight to include in the framework

questionstring

The original user question that led to this framework request plus any relevant chat history context. Used to select columns to aggregate over in the final insight response.

Optional

aggregatestring

Aggregation type (sum, mean, count_distinct). Pass a value from the insight's known aggregate options when available. Default None is valid for insights with no aggregate options.

Default: null

Get Entities from Insight

get_entities_from_insight

Full Description

Get entities related to a specific insight.

Retrieves entities associated with a particular insight. Useful for exploring what entities are involved in a specific insight or understanding insight-entity relationships.

Valid entity_representation values: abundle, actor, aingredient, app, apublisher, artist, category, cbsa, city, clfiling, clopinion, company, country, dccategory, ddcategory, director, distributor, dma, dtcategory, educationlevel, entertainer, ethnicity, finished, franchise, gender, generation, genre, judge, label, lawyer, league, legalmatter, maritalstatus, medicalsegment, mine, occupation, pcodecategory, plabel, platform, port, product, raw, region, retailer, service, socialhandle, song, sport, state, team, ticker, title, transformed, us, vehiclebody, vehiclemake, vehiclemodel, venue, website, ww, yearlyincome, zip

Parameters (2 required, 1 optional)

Required

entity_representationstring

Entity type/category to filter entities. Valid values: 'abundle' (App Bundle), 'actor' (Actor), 'aingredient' (Active Ingredient), 'app' (App), 'apublisher' (App Publisher), 'artist' (Artist), 'category' (Category), 'cbsa' (CBSA), 'city' (City), 'clfiling' (CLFiling), 'clopinion' (CLOpinion), 'company' (Company), 'country' (Country), 'dccategory' (Document Content Category), 'ddcategory' (Document Domain Category), 'director' (Director), 'distributor' (Music Distributor), 'dma' (DMA), 'dtcategory' (Document Type Category), 'educationlevel' (Education Level), 'entertainer' (Entertainer), 'ethnicity' (Ethnicity), 'finished' (Finished Commodity), 'franchise' (Franchise), 'gender' (Gender), 'generation' (Generation), 'genre' (Genre), 'judge' (Judge), 'label' (Music Label), 'lawyer' (Lawyer), 'league' (League), 'legalmatter' (Legal Matter), 'maritalstatus' (Marital Status), 'medicalsegment' (Medical Segment), 'mine' (Mine), 'occupation' (Occupation), 'pcodecategory' (Procedure Code Category), 'plabel' (Private Label Brand), 'platform' (Platform), 'port' (Port), 'product' (Product Brand), 'raw' (Raw Commodity), 'region' (Region), 'retailer' (Retailer Banner Brand), 'service' (Service Brand), 'socialhandle' (Social Handle), 'song' (Song), 'sport' (Sport), 'state' (State), 'team' (Team), 'ticker' (Ticker), 'title' (Title), 'transformed' (Transformed Commodity), 'us' (US), 'vehiclebody' (Vehicle Body Style), 'vehiclemake' (Vehicle Make Brand), 'vehiclemodel' (Vehicle Model Brand), 'venue' (Venue), 'website' (Website), 'ww' (Worldwide), 'yearlyincome' (Income), 'zip' (Zip Code)

insight_idinteger

Unique identifier for the insight you want to explore

Optional

limitinteger

Maximum number of entities to return

Default: 100

Get Insights from Entity

get_insights_from_entity

Full Description

Get insights related to a specific entity.

Retrieves insights associated with a particular entity (e.g., company, state, retailer). Useful for exploring what data is available for a specific entity or understanding entity-insight relationships.

Parameters (2 required, 1 optional)

Required

entity_idinteger

Unique identifier for the entity you want to analyze

entity_representationstring

Entity type/category to filter insights. Valid values: 'abundle' (App Bundle), 'actor' (Actor), 'aingredient' (Active Ingredient), 'app' (App), 'apublisher' (App Publisher), 'artist' (Artist), 'category' (Category), 'cbsa' (CBSA), 'city' (City), 'clfiling' (CLFiling), 'clopinion' (CLOpinion), 'company' (Company), 'country' (Country), 'dccategory' (Document Content Category), 'ddcategory' (Document Domain Category), 'director' (Director), 'distributor' (Music Distributor), 'dma' (DMA), 'dtcategory' (Document Type Category), 'educationlevel' (Education Level), 'entertainer' (Entertainer), 'ethnicity' (Ethnicity), 'finished' (Finished Commodity), 'franchise' (Franchise), 'gender' (Gender), 'generation' (Generation), 'genre' (Genre), 'judge' (Judge), 'label' (Music Label), 'lawyer' (Lawyer), 'league' (League), 'legalmatter' (Legal Matter), 'maritalstatus' (Marital Status), 'medicalsegment' (Medical Segment), 'mine' (Mine), 'occupation' (Occupation), 'pcodecategory' (Procedure Code Category), 'plabel' (Private Label Brand), 'platform' (Platform), 'port' (Port), 'product' (Product Brand), 'raw' (Raw Commodity), 'region' (Region), 'retailer' (Retailer Banner Brand), 'service' (Service Brand), 'socialhandle' (Social Handle), 'song' (Song), 'sport' (Sport), 'state' (State), 'team' (Team), 'ticker' (Ticker), 'title' (Title), 'transformed' (Transformed Commodity), 'us' (US), 'vehiclebody' (Vehicle Body Style), 'vehiclemake' (Vehicle Make Brand), 'vehiclemodel' (Vehicle Model Brand), 'venue' (Venue), 'website' (Website), 'ww' (Worldwide), 'yearlyincome' (Income), 'zip' (Zip Code)

Optional

limitinteger

Maximum number of insights to return

Default: 100

Search Entities

search_entities

Full Description

Search for entities by name or description.

Optionally filter by entity_representation to narrow results to a specific entity type. See the entity_representation parameter for valid values.

Parameters (1 required, 2 optional)

Required

querystring

Search for entities by name or description

Optional

entity_representationstring

Filter results to a specific entity representation type. Valid values: 'abundle' (App Bundle), 'actor' (Actor), 'aingredient' (Active Ingredient), 'app' (App), 'apublisher' (App Publisher), 'artist' (Artist), 'category' (Category), 'cbsa' (CBSA), 'city' (City), 'clfiling' (CLFiling), 'clopinion' (CLOpinion), 'company' (Company), 'country' (Country), 'dccategory' (Document Content Category), 'ddcategory' (Document Domain Category), 'director' (Director), 'distributor' (Music Distributor), 'dma' (DMA), 'dtcategory' (Document Type Category), 'educationlevel' (Education Level), 'entertainer' (Entertainer), 'ethnicity' (Ethnicity), 'finished' (Finished Commodity), 'franchise' (Franchise), 'gender' (Gender), 'generation' (Generation), 'genre' (Genre), 'judge' (Judge), 'label' (Music Label), 'lawyer' (Lawyer), 'league' (League), 'legalmatter' (Legal Matter), 'maritalstatus' (Marital Status), 'medicalsegment' (Medical Segment), 'mine' (Mine), 'occupation' (Occupation), 'pcodecategory' (Procedure Code Category), 'plabel' (Private Label Brand), 'platform' (Platform), 'port' (Port), 'product' (Product Brand), 'raw' (Raw Commodity), 'region' (Region), 'retailer' (Retailer Banner Brand), 'service' (Service Brand), 'socialhandle' (Social Handle), 'song' (Song), 'sport' (Sport), 'state' (State), 'team' (Team), 'ticker' (Ticker), 'title' (Title), 'transformed' (Transformed Commodity), 'us' (US), 'vehiclebody' (Vehicle Body Style), 'vehiclemake' (Vehicle Make Brand), 'vehiclemodel' (Vehicle Model Brand), 'venue' (Venue), 'website' (Website), 'ww' (Worldwide), 'yearlyincome' (Income), 'zip' (Zip Code)

Default: null

limitinteger

Maximum number of entities to return

Default: 10

Search Insights

search_insights

Full Description

Search for insights by name or description.

Parameters (1 required, 1 optional)

Required

querystring

Search for insights by name or description

Optional

limitinteger

Maximum number of insights to return

Default: 10

Convert Text to Insight

text_to_insight

Full Description

Convert natural language questions into structured analytical frameworks and insights.

This tool transforms business questions into data queries and returns results in markdown table format. It automatically identifies relevant entities, metrics, and filters based on your question.

Common Use Cases:

Revenue and spend analysis by company, region, or time period
Growth metrics and trend analysis
Comparative analysis across entities and insights
Performance benchmarking and ranking across entities and insights

Not Suitable For:

Data discovery questions: "What data is available for Walmart?"
Data discovery questions: "What fields can I filter on?"

Parameters (1 required)

Required

questionstring

A business question about data you want to explore and analyze. Examples: 'Show me Walmart Card Spend in 2024', 'What were the top 10 companies in FL last year?'

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