ChatGPT Plugin

Cargo

Your GTM in ChatGPT

Brand: Cargo

Category: Sales & CRM
Primary Subcategory: AI Workflow Automation & iPaaS Platforms

Integration details

Description

Cargo is GTM infrastructure for AI assistants. Connect this MCP server and ChatGPT can operate your Cargo workspace: discover and run actions across 130+ integrations, execute tools and agents, query CRM and revenue models, and read the playbooks and ICP context your team already wrote. Sign in with OAuth — no API key to paste. Your session binds to one workspace, so ChatGPT sees your integrations, your models, and your credits. What you can do from chat: • Search the action catalog and see credit cost before anything runs • Enrich people and companies, look up CRM records, and call native platform ops • Run a single action or a batch across many records • Query workspace models (selects, joins, aggregates) • Read workspace context — ICP definitions, playbooks, rubrics — before guessing Ask in plain English. ChatGPT finds the right action, confirms cost when it matters, and brings results back into the conversation. Best for RevOps, sales ops, and GTM engineers who want research-to-action without leaving chat. Building multi-step workflows or workspace-as-code stays in the Cargo CLI — this connector is the runtime for in-conversation work. Learn more: https://www.getcargo.ai/mcp

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Sales & CRM
Primary Subcategory: AI Workflow Automation & iPaaS Platforms
Secondary Subcategories: None listed
Brand: Cargo
Access: Account required
First tracked: 2026-09-10
Tool count: 17
Geography: US

Agent DiscoverabilityChatGPT Plugin Discovery Score

ChatGPT organic discovery is live

Your score is coming

ChatGPT now suggests Plugins on its own when they match a user's request.Your Plugin Discovery Score measures how often yours appears, and it will show here as soon as it’s ready.

ChatGPT recommends Airtable when a user asks it to update a CRM. — ChatGPT surfaces Airtable because it matches the user's request.

Primary Subcategory

Competing in ChatGPT AI Workflow Automation & iPaaS Platforms

View Category

Listed in alphabetical order

Primary Subcategory

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Tools

17 tools agents can invoke

Resolve autocomplete options for a connector action (HubSpot object types, Slack channels, Metabase questions, …). Pass slug from search_actions.autocompletes. Resolve params to concrete values first — do not pass $this expression paths. Put chosen values in execute_action data, not action.config.
autocomplete_action
List the files and folders at a path in the workspace context. Pass depth -1 with no path for the full tree in one call. Navigates structure without reading any content.
browse_context
Return a model's columns, dataset slug, and unquoted dataset.model reference without querying rows.
describe_model
Run one action on a single input. Creates a run and consumes credits. If the result is outcome executing, poll with get_run. Do not loop this over a list — use execute_action_batch.
execute_action
Run one action over many records in a single batch. Cheaper and observable than looping execute_action. If the result is outcome executing, poll with get_batch.
execute_action_batch
Resolve the input and output JSON schemas of a connector, native, tool, or agent action without executing it. Pass the action object from search_actions. For connector fields that need a picked id (list, object type, campaign), call autocomplete_action.
get_action_schema
Get one batch by uuid. If execute_action_batch returned outcome "executing", call this until the batch has finished. A finished batch includes one page of the CSV in data.text. Pass offset and limit to read further pages (limit default 100, max 100). If truncated is true, call again with the next offset. totalRows is the total when this page reaches the end of the file. Read data.text. Do not fetch the URL. Does not return the raw batch record or internal storage keys.
get_batch
Get one run by uuid. Returns the same shape as execute_action: the last node output, run uuid, and credits used. If execute_action returned outcome "executing", call this until the run has finished. Does not return computed configs, execution traces, or other debug payloads.
get_run
Credit usage for the last 7 days, grouped by integration. Check this before running paid actions.
get_usage
List data models in this workspace. Use describe_model then query_models.
list_models
List recent ad-hoc action runs in this workspace. Does not include play or tool workflow runs.
list_runs
List every indexed file in the workspace context (path, title, summary, folder) without reading any file body. The context is the workspace's knowledge base — playbooks, ICP definitions, scoring rubrics, internal docs. Start here to discover what exists, then search_context or read_context for the parts the task needs. This surface is read-only; write through the workspace's context capability.
map_context
Run one read-only SQL SELECT over this workspace's models. Reference a model as dataset.model — take the exact reference from describe_model. Joins, aggregates and CTEs are allowed; anything other than SELECT is refused. Aggregate rather than paging: the row cap is small.
query_models
Read a UTF-8 file from the workspace context. Reads with no endLine return only the first 250 lines and set truncated; pass a 1-indexed inclusive startLine/endLine range to page through the rest or target a section. The response always carries totalLines.
read_context
Search actions you can run: integration catalog (connector), Cargo native, workspace tools, and agents. Each result includes autocompletes when input fields need a picked id. Use the returned action with execute_action or execute_action_batch, get_action_schema, and autocomplete_action. Never fan out execute_action record-by-record — use execute_action_batch.
search_actions
Search context file contents and return matching lines (path, line number, snippet), never whole files. At most 5 matches per file, so results spread across files. Use it to locate a term, then read_context a tight range around the hits.
search_context
Return the signed-in user, the workspace this MCP session is bound to, and a plan/credits snapshot.
whoami

FAQs

Cargo ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve Cargo's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are Cargo alternatives on ChatGPT?

As of 2026-10-24, Cargo competes with AB Projects, Ace Work, Activepieces, Adagio, Adobe CX Enterprise Coworker, Automo, AutoRFP.ai, Carly and 21 more in ChatGPT AI Workflow Automation & iPaaS Platforms, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.