Improvado AI Agent

Improvado AI Agent helps users work with Improvado workspaces through ChatGPT: inspect workspaces, data sources, connections, extracts, loads, documents, dashboards, recipes, and Discovery API workflows; switch workspace context; query data; and create or update private workspace resources.

View in the ChatGPT registry

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Data & Analytics
Primary Subcategory: Marketing & Commerce Data Integration
Secondary Subcategories: None listed
Brand: Improvado
Access: Account required
First tracked: 2026-06-11
Tool count: 93
Geography: US

ChatGPT Plugin Discoverability Score

ChatGPT organic discovery is not live yet

Improvado AI Agent is tracked in the ChatGPT Plugin registry. Public organic-discovery measurement is not live for ChatGPT yet, so there is no score to publish today.

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Primary Subcategory

Competing in ChatGPT Marketing & Commerce Data Integration

View Category

Listed in alphabetical order

Primary Subcategory

AdzviserOrganic discovery is pendingGet the score at launch

CatchrOrganic discovery is pendingGet the score at launch

Coupler.ioOrganic discovery is pendingGet the score at launch

DataslayerOrganic discovery is pendingGet the score at launch

FeedoptimiseOrganic discovery is pendingGet the score at launch

Improvado AI AgentOrganic discovery is pendingGet the score at launch

Score explained

How the Discoverability Score works

Organic discovery scoring for Improvado AI Agent on ChatGPT is not live yet. The score will use measured agent conversations when it launches.

InvisibleBuriedEmergingCompetitiveWinning

Organic discovery scoring is pending. Your Plugin score will appear on this scale when measurement goes live.

FoundDiagnostic

Whether Claude found your Plugin in connector search. It must be Found before it can reach the picker, but the score counts picker appearances—not search results.

PickedMain score

How often your Plugin appeared in the picker, or Claude invoked it directly, across contested conversations. This percentage is the Discoverability Score; the headline number is rounded.

PositionedDiagnostic

What position your Plugin appeared in when it was shown in the picker. This shows prominence, but it does not affect the score.

Read the full scoring methodology Recommended guideHow to get your Claude Connector organically discoveredFollow the practical steps agents use to find, shortlist, and choose your Connector.

Tools

93 tools agents can invoke

Activate a recipe (promote to production)
Execute SQL queries against ClickHouse database to retrieve or analyze data
Creates a new DTS connection for a data source using the current user's context. This ensures the connection is created with proper permissions and workspace isolation. First use 'integration_maker_get_data_source_authentications' to get available auth_ids and required parameters. Returns the connection_id on success.
Create a new document with title, content, and optional tags. Returns the created document with its ID.
Create a custom extraction template based on a parent global template. Works for both entity and wide report templates. For wide templates (parent has allow_to_select_dimensions=True), connection_id is REQUIRED; for entity report templates, connection_id is NOT needed. TIP: When creating extracts for "wide" data sources, the standard createExtractTool may lack field validation. Instead, first create a custom template with this tool (which validates fields, dimensions, and additional_params), then create an extract based on the resulting custom template ID.
Create a new data extract from a data source
Create a NEW flat data extract from an uploaded file. This is the final step in the NEW file import flow - it creates a persistent extract configuration that stores the data. To upload a file to an EXISTING extract, use uploadNewFileToExtractTool instead.
Create a new LES integration (sandbox + YAML generation + upload + agency registration) and stream progress into the chat side panel. Use when the user asks to add a new data source (e.g. "Create Trello integration"). To retry a failed attempt, pass resume_from_job_id and optionally hint — only do so when you have a concrete fix in mind; otherwise surface the error to the user.
Create a new data load to a destination
Create or replace MDG view in agency schema. Use CREATE OR REPLACE to update existing rules.
Create a new recipe step (cell). Currently supports only SQL steps.
Create a recipe from a template
Create a Google Sheets extract using the flat data API
Create a SQL extract from a connection + table (or custom query). This is the final step — it persists the extract config and schedules recurring pulls. Run field discovery and sample first so the user confirms the schema.
Show the custom connector / integration creation form to the user. DO NOT call this tool if the user's message already contains a credential_ref (e.g., 'Use credential_ref="uuid" to retrieve stored credentials'). Credentials are already stored server-side and the form would be redundant — call createLesIntegrationChatTool directly with the credential_ref and data_source extracted from the message instead. Use this tool when the user wants to create, build, add, or request a new integration or connector for ANY data source AND no credential_ref has been supplied. The form collects data source name, API credentials, documentation link, and additional requirements. After the user submits, the integration creation process starts automatically. This is the default first step for integration creation when no credentials have been provided yet. If the user already mentioned the data source name or documentation link, pre-fill those non-sensitive fields. The user always types secrets fresh into the form — do NOT pass api_key/password/client_secret/login/client_id parameters even if the user mentioned them in chat.
Permanently delete a document and all its versions. This action cannot be undone.
Delete a data load
Delete a scheduled chat belonging to the current chat. Permanently removes the scheduled chat and stops any future executions. Only schedules owned by the current chat can be deleted via this tool.
Discover field definitions (column names, types) from an uploaded flat data file. Uses the DTS field discovery API to analyze the file and return inferred field schemas.
Discover field definitions (column names, suggested and possible types, dimension/metric) from a SQL table or custom query. Call this after the user picks a table from listSqlReportTypesTool.
Download a file from a data source API via secret proxy and save it to storage. Unlike discoveryRequestTool which loads the full response content into the conversation context, this tool uploads the response to storage and returns a signed URL so you can download the file directly to disk using curl. Use this for binary data (Excel, PDF, ZIP, images), large CSV exports, or any response you want saved as a file without consuming context window. Returns a signed download URL valid for 1 hour.
List all accounts with optional filtering and pagination. Supports filtering by connection ID, active status, search terms, and ordering.
List all connectors for a given datasource
Display a grid of available data sources that users can connect to Improvado. Shows data sources with logos, categories, and connect buttons. Use this when user wants to see or connect data sources. Optionally filter by category.
Call the Improvado Discovery API for a given datasource and connector to fetch live data from a platform (Facebook, Google Ads, TikTok, LinkedIn, etc.). CRITICAL — read the /discovery skill for the full protocol. Quick rules: - `request.url` MUST be an absolute URL with scheme (shape: https://graph.facebook.com/v<VERSION>/act_<id>/insights — version resolved via the protocol below, not hardcoded). Relative paths like /me/adaccounts or /act_<id>/campaigns return 400 "discovery URL ... is not allowed". - Verify the latest non-deprecated API version from the official changelog (via discoveryWebSearchTool + retrieveDocumentationTool) BEFORE calling — never guess versions, and never reuse a version from a prior example. - Ask the user to pick a `connectorId` from discoveryListConnectorsTool — do not invent or assume connectors. - For endpoints that need an account, get the account id from discoveryListAccountsTool first.
Execute OpenAI Assistant API calls to interact with a specific assistant
Edit an existing document. Updates create a new version. You can update title, content, and/or tags.
Search for chats across the agency. This tool returns a list of chats that match the search criteria.
Generate a data preview (sample rows) for an uploaded flat data file using the specified field definitions. Use this after discovering fields and confirming the schema with the user.
Generate a data preview (sample rows) for a Google Spreadsheet tab using specified field definitions. Use after getSpreadsheetSchemaTool to confirm the schema with the user.
Generate a data preview (sample rows) for a SQL table / custom query using the specified field definitions. Use this after field discovery so the user can confirm the schema before creating the extract.
Get a chat by ID. This tool retrieves the full information of a specific chat by its ID.
View accounts associated with a specific data source connection
View your data source connections
Get the currently active workspace context.
Get a specific dashboard configuration by ID. Returns full dashboard settings including complete config JSON, URL, title, and all metadata. The dashboard must belong to the current agency. For editing or building dashboards, see the `business-intelligence-editor` skill — it provides a full CLI (`frontend-cli.py`) for dashboard work.
View connections for a specific destination
Get full details of a specific document by ID, including its content.
Get detailed information about a specific extract - NOTE: Currently broken due to Improvado API bug
Get lightweight status information about a specific extract (id, status, last_sync, error_text, title). Use this instead of getExtractByIdTool when you only need to check extract status.
View details of a specific extract template
View available extract templates for a specific data source
View details of a specific data load
View your data loads for a specific destination
Get credentials (host, port, login, password) for a managed SFTP or S3 connection. Use after getting or creating a managed_sftp / managed_s3 connection to show the user how to connect.
Fetch an MDG rule example from the library. If rule_name is omitted, returns available rule names.
Fetch a single recipe step (cell) with metadata and last-run SQL
List available recipe templates
Fetch a single transformation recipe with minimal metadata and steps
Get scheduled chats. By default returns only schedules belonging to the current chat. Set scope to "workspace" to list all schedules in the workspace.

Improvado AI Agent FAQ

How do I improve a ChatGPT Plugin's 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 Improvado AI Agent alternatives on ChatGPT?

As of 2026-08-14, Improvado AI Agent competes with Adzviser, Catchr, Coupler.io, Dataslayer, Feedoptimise, Funnel, Lytical, Master Metrics, Polar Analytics, Quanti IA, Windsor.ai in ChatGPT Marketing & Commerce Data Integration, 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.