Enterprise DNA
M MCP Servers Developer low

decidefyi/decide

by Various

Deterministic refund, cancel, trial, and return policy decisions for support teams. One verdict for humans and AI agents via API + MCP with request-level audit trail.

D

MCP

decidefyi/decide

Added 1 June 2026

Overview

A deterministic rule engine that returns refund, cancel, trial, and return policy decisions for support teams. It exposes an API and MCP interface to deliver a single verdict for both human agents and AI agents, with a request-level audit trail.

Best for

Best for
Support teams needing a consistent, auditable policy engine for common customer service decisions

Use cases

  • Automating refund eligibility checks in customer support workflows
  • Enforcing consistent cancellation policies across AI and human agents
  • Auditing policy decisions with per-request trail for compliance

Notes

A deterministic rule engine that returns refund, cancel, trial, and return policy decisions for support teams. It exposes an API and MCP interface to deliver a single verdict for both human agents and AI agents, with a request-level audit trail.

0 stars on GitHub. Last updated 2026-06-01.

Use cases

  • Automating refund eligibility checks in customer support workflows
  • Enforcing consistent cancellation policies across AI and human agents
  • Auditing policy decisions with per-request trail for compliance

Pros

  • Deterministic output eliminates ambiguity in policy enforcement
  • Audit trail provides transparency for every decision
  • Simple API and MCP integration for both humans and AI agents

Cons

  • Limited to refund, cancel, trial, and return policies only
  • Zero GitHub stars suggests early stage or low adoption
  • Deterministic rules may miss nuanced edge cases without manual updates

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Deterministic output eliminates ambiguity in policy enforcement
  • Audit trail provides transparency for every decision
  • Simple API and MCP integration for both humans and AI agents

Cons

  • Limited to refund, cancel, trial, and return policies only
  • Zero GitHub stars suggests early stage or low adoption
  • Deterministic rules may miss nuanced edge cases without manual updates

Pairs with

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