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Crypto Exchange Onboarding with Claude: An Operator Decision Sequence

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
1,375
Company Posts That Month
20
Language
English
Hacker News Points
-
Post removed?
No
Summary

The text outlines a detailed process for managing onboarding and compliance decisions in a crypto exchange using the Didit Model Context Protocol (MCP) server and the Claude tool. The process begins with establishing the operating context and selecting an appropriate verification workflow for each customer, which is crucial for subsequent Know Your Customer (KYC) checks. Customers complete identity verification through Didit's hosted UI, and results are reviewed manually against the exchange's policies. Anti-Money Laundering (AML) checks follow, requiring careful interpretation of results, and wallet screening assesses the risk without automatically controlling funds. The process culminates in transaction submission for monitoring, where the transaction's category-specific details dictate the schema. The Business Console handles policy authoring and rule configuration, ensuring that Claude supports operators without replacing human compliance oversight. The entire system relies on a methodical sequence of evidence gathering, policy application, and explicit actions, with clear boundaries between automated processes and operator decisions.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
MCP 13 1,562 186 99 -80%
AI Coding Assistant 2 276 77 47 -83%
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