TextForge: A Claude Code-built email approval tool for LLM workflows

✍️ OpenClawRadar📅 Published: March 14, 2026🔗 Source
TextForge: A Claude Code-built email approval tool for LLM workflows
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TextForge is a tool built entirely with Claude Code that provides mandatory approval gates for email workflows, preventing Claude or any other LLM from sending emails without explicit user approval. The developer created it to automate 8-10 hours per week of email-driven business processes while maintaining control over sensitive B2B communications.

Development Process

The project started with a self-hosted MCP server + HTTP API using a private Google Cloud API key scoped to the developer's domain. This initial version took about 5 days to build and included:

  • A CLI for Pipedrive that could access deals and task lists
  • A Claude Code skill that combined the Pipedrive CLI with the email system
  • 2-3 months of refinement for threading, signatures, and MIME handling

Key Features

  • Email draft list and approval queue ("pull request review for outbound emails")
  • Webhook support for approve/reject without opening the app
  • Attachment support with ClamAV anti-virus scanning
  • Secure pass-through architecture that doesn't retain data
  • Selective sync capabilities
  • Integration with Pipedrive CRM
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Security Implementation

To meet Google's CASA2 audit requirements for email reading scopes:

  • Used Claude to run an OpenProse workflow scanning the ASP .NET Core app for OWASP vulnerabilities
  • Fixed vulnerabilities before Google's security audit partners reviewed the application
  • Deployed ClamAV instance using Claude Code + Pulumi for attachment scanning
  • The audit process took several weeks and required thorough security review

Development Approach

The developer wrote minimal code manually, instead focusing on:

  • Writing PRDs and tech specs
  • Planning RALPH loops and OpenProse workflows
  • Approving mock-ups and UI designs
  • Testing the application

The tool improved business metrics including close rate and ARR aging by enabling more frequent follow-ups while maintaining security controls.

📖 Read the full source: r/ClaudeAI

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👀 See Also