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Claude or ChatGPT for Identity Workflows: What Actually Differs

Blog post from Didit

Aggregate trend data notice

Excluded from normalized aggregate trends after staff review: 3056 posts were attributed to March 2026; 671 shared March 14, 2026. The preceding six-month median was 13.5 posts.

Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.

This company's pages remain public, but its content is excluded from normalized aggregate trends. Unfiltered raw trends and advanced filtering are available to Accelerate and Lead accounts.

Post Details
Company
Date Published
Author
Didit
Word Count
1,524
Company Posts That Month
43
Language
English
Hacker News Points
-
Post removed?
No
Summary

Claude and ChatGPT can both connect to the Didit Model Context Protocol (MCP) service, but they access different tool catalogues due to endpoint policies rather than inherent limitations. Claude's connection grants access to 115 tools, including those for direct document and biometric checks, while ChatGPT's OpenAI app surface offers a restricted catalogue of 101 tools, excluding certain operations to maintain tighter data-input boundaries. Both utilize OAuth 2.1 with PKCE for authentication, and neither requires users to paste server application keys into chat. The choice between the two depends on the specific operational needs: Claude is suitable for broader authorized operations requiring direct checks, whereas ChatGPT is apt for workflows that fit public-app review boundaries and minimize raw personal data entry. Both clients can interact with a remote MCP server, but the practical differences lie in the contracts Didit exposes to each, with ChatGPT focused on conversational investigation and orchestration without raw biometric or document inputs.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
MCP 25 8,729 854 211 -20%
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Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.