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MCP for KYC: Run Identity Verification in Natural Language

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
1,154
Company Posts That Month
121
Language
English
Hacker News Points
-
Post removed?
No
Summary

Didit's Model Context Protocol (MCP) server simplifies the Know Your Customer (KYC) verification process by allowing AI agents to create sessions, generate verification links, and poll decisions using natural language prompts, eliminating the need for manual coding with webhooks or polling endpoints. The MCP server, an open standard published under the MIT license, supports over 130 tools across various categories such as identity checks, fraud detection, and transaction monitoring, accessible via Streamable HTTP. Authentication is managed through OAuth 2.1 with PKCE, ensuring user-scoped access without requiring API keys. A full KYC verification, including ID document checks, passive liveness, and face matching, costs $0.33 per session, with users receiving 500 free verifications per month. Didit, backed by Y Combinator and operational in over 220 countries, offers a scalable solution for both prototyping and production-level identity verification workflows, enabling seamless integration with AI agents through a streamlined setup process.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
MCP 38 10,922 895 210 +41%
AI Agents 3 6,829 1,441 261 +10%
Use This Data

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.