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.
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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