Data Parrot

Data Parrot MCP for HubSpot Data Parrot brings AI revenue analysis of your HubSpot data into your AI tools.

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What it can do

  • Get Data Parrot Access Status: Report this MCP connection's workspace-access state.
  • Select Data Parrot Workspace: Bind this MCP connection to one Data Parrot workspace after the user explicitly chooses from workspace_options returned by get_data_parrot_access_status. Never choose a w
  • Switch Data Parrot Workspace: Switch only to a workspace the user selected from workspace_options.

What data it sees

Do you need an account

No: the server works without sign-in

Data Parrot MCP for HubSpot

Data Parrot brings AI revenue analysis of your HubSpot data into your AI tools.

Data Parrot connects to HubSpot and learns how your company sells. Its MCP server brings deal health, sales forecasting, pipeline analysis, customer health, and win/loss analysis into your AI tools.

Ask your AI tool about your HubSpot forecast, pipeline, deals, sales activity, customer health, and win/loss using analysis Data Parrot has already completed.

Get a Data Parrot account · Visit Data Parrot · MCP documentation · Connection guide · Prompt library

How to connect

How to connect Data Parrot to Claude

The server address to paste into Claude settings:

https://data-parrot--dataparrot.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Data Parrot to ChatGPT

The server address to paste into ChatGPT settings:

https://data-parrot--dataparrot.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Data Parrot to Cursor

The server address to paste into Cursor settings:

https://data-parrot--dataparrot.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (14)

Raw names from tools/list. Only developers need these.

get_data_parrot_access_statusReport this MCP connection's workspace-access state.
select_data_parrot_workspaceBind this MCP connection to one Data Parrot workspace after the user explicitly chooses from workspace_options returned by get_data_parrot_access_status. Never choose a workspace for the user.
switch_data_parrot_workspaceSwitch only to a workspace the user selected from workspace_options.
reset_data_parrot_workspace_bindingAfter the user explicitly agrees, reset this MCP connection's unavailable workspace binding so they can choose from their currently active Data Parrot workspaces.
describe_data_catalogDiscover what Data Parrot knows about this workspace and how to retrieve it. Call with no arguments for the compact master manifest, then use an advertised section and detail for focused fields, values, tenant-defined properties, and business meaning. This tool describes data; it does not return business evidence.
get_dealsSearch, filter, count activity, group, rank, and return open/won/lost CRM deals. Open deals include manual forecast_status and AI forecast_category. Choose one owner selector. For broader AI analysis, inspect deals/analysis_concepts in the catalog.
get_dealReturn details for one known deal ID, including selectable HubSpot fields, custom properties, associations, the seller-entered next step and future scheduled activities, and Data Parrot AI analysis for open deals. Use it for deal details, forecast confidence, or that deal’s recorded won/lost reason.
get_deal_timelineInspect one known deal’s reverse-chronological timeline of Data Parrot AI assessments, CRM changes, and customer engagements.
get_engagementsReturn date-bounded activities or deal/lead CRM object events. For activities associated with deals or leads, use meetings, calls, emails, or communications plus association filters.
get_pipeline_historyReturn pipeline history for one concrete inclusive date range. For comparisons, call once per range with identical non-date arguments; align by explicit ranges and returned order, and treat unavailable history as missing, not zero.
get_forecastReturn exact open-deal totals, configured manual forecast_status, and AI assessments. forecast_status is manual; forecast_category is AI. Closed deals are excluded. For target-attainment questions, consider won deals from the same scope and date range, plus lost deals when explaining a shortfall; get_deals returns those deal sets, get_win_loss explains outcomes, and get_deal provides one deal’s details.
get_companiesReturn exact Customer Health KPIs plus paginated company rows or count groups. For ranked risk lists, state the ranking basis; call partial rows the highest-ranked returned accounts. Do not sum company financial values. Use get_deals for open expansion opportunities.
get_win_lossReturn Data Parrot closed-deal analysis grouped into win/loss reasons, sales performance factors, and buyer decision factors, with attribution, ranking, and supporting-deal evidence.
expand_resultLoad more data or supporting evidence from a prior Data Parrot result. Use its result_id and one returned continuation_id; its query settings are preserved.