Data analysts rarely work from one clean source. A typical investigation may depend on a spreadsheet in Drive, transformation logic in GitHub, a metric definition in SharePoint, CRM records in HubSpot, and the Slack discussion that explains why a number changed. This guide identifies which published AI connections can retrieve that context—and keeps file access, record retrieval, code access, and database query execution as separate capabilities.
●39 published connectionsLast verified 1 Aug 2026Written and researched by Christian Stewart, Founder and Editor
The most useful verified connectors for analysts currently fall into five groups: file storage for workbooks and exports, developer tools for SQL and transformation code, knowledge management for metric definitions, CRM for customer and pipeline records, and communication tools for decision context. The main selection consideration is whether a documented connection covers the action you need — creating or updating records, not only search and read — on the assistant and plan your organization has already approved.
Most useful types
File storage, Productivity, Developer tools, Knowledge management, CRM and Communication
Verified connections
39 published records
Assistants covered
Claude, ChatGPT and Gemini
Selection consideration
Confirmed write/action support, not just read access
The most useful verified connectors for analysts currently fall into five groups: file storage for workbooks and exports, developer tools for SQL and transformation code, knowledge management for metric definitions, CRM for customer and pipeline records, and communication tools for decision context. Google Drive, Microsoft SharePoint, GitHub, HubSpot, and Slack all have relevant published pairings in the Connector Scout dataset. None of those pairings should be described as a general-purpose data-warehouse connector. Treat SQL execution, live BI querying, and database write access as unverified unless a dedicated connection record explicitly documents them.
What this guide covers
This guide covers connectors that link AI platforms to the applications and data sources used in this profession. It does not rank standalone AI tools or general-purpose AI software.
What this role needs from a connector
Each responsibility maps to a connector category and the capability a connection must document before it can help.
Responsibilities of a data analyst, the connector category each one depends on, the capability required, and any verified example connections.
Connector Scout has published 13 verified connections relevant to this role on ChatGPT. OpenAI's assistant, extended through the Plugin Directory, where plugins bundle skills and connected apps built on the Apps SDK.
Connector Scout has published 13 verified connections relevant to this role on Claude. Anthropic's assistant, extended through first-party connectors and through custom connectors backed by remote MCP servers.
Connector Scout has published 13 verified connections relevant to this role on Gemini. Google's assistant, where access to business data is governed largely by Google Workspace administration rather than by an in-product gallery.
A SharePoint scope containing the approved metric documentation
A Drive scope containing the working files for the analysis
Limitations
No warehouse or BI execution is implied
Retrieved files may be stale or incomplete
Row-level sensitive data should remain in approved analysis systems unless policy explicitly allows retrieval
The model's explanation still requires analyst review
How to choose
Capability boundaries
Reading a spreadsheet does not prove live database access. Reading SQL from GitHub does not execute it. Reading CRM records does not grant access to an unrelated BI tool. Searching Slack does not validate the conclusion found in a message.
Distinguish file retrieval from query execution
Reading a workbook or a repository file is a retrieval capability. Running a query is an action capability against a different system, recorded separately on each record.
Prefer read-only access and least privilege
Analysis work almost never needs write access. Where a connection offers both, authenticate with a read-only role and the narrowest scope that covers the work.
Verify whether knowledge content is synced or retrieved on demand
A connection that indexes an entire workspace will surface drafts and deprecated definitions alongside current ones. Each record states whether content is synced or fetched at request time.
Knowledge management
Confirm admin controls, plan, region, and residency per record
Plan requirements, administrator approval, regional availability, and residency are recorded on the individual connection record, not per platform. Where a field is unverified, assume nothing.
Decide whether a native connection, MCP server, or custom API is acceptable
Warehouse and BI access is most commonly reached through MCP servers or API workflows rather than first-party connections, which shifts responsibility for hosting, authentication, permissions, and logging to the implementer.
Re-check stale records before a connector becomes a dependency
Connector capabilities in this space change quickly. Every record carries a last-verified and a next-review date; re-check before making it a production dependency.
Security and data-access considerations
Grant the narrowest scope that supports the analysis; a connection that reads a folder reads whatever personal data is in it.
Access is bounded by the source system's own permissions, so who connects an application decides how much of it the assistant can reach.
Customer-level records and personnel or financial extracts are often stored beside routine analysis files and need separate handling.
Secrets committed to analytics repositories are retrieved as readily as any other file; connecting a repository does not filter them out.
Aggregation reduces but does not remove disclosure risk in small populations.
Review retention and data-residency implications per connection before retrieval becomes routine.
A retrieved explanation is not a validated result; a human verifies numbers before a decision is made on them.
Connections that bring briefs, CRM records, campaign discussion, and reporting exports into an AI assistant — and what each one is documented to change.
File storageKnowledge managementCRM
45 published connections·Last verified 31 Jul 2026
Verified connections that bring repository files, engineering discussion, and technical documentation into ChatGPT, Claude, and Gemini — and the exact point where retrieval stops and code execution would begin.