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Finology-tech/finology-mcp

by Various

Deterministic 2026 federal student loan repayment math for AI agents. RAP, IBR, ICR, PSLF and plan eligibility from Finology Software's parity-verified engine.

MCP

Finology-tech/finology-mcp

Added 9 Oct 2026

#chatgpt #claude #financial-advisors #fintech #mcp #mcp-server #model-context-protocol #student-loans

Overview

MCP server that provides deterministic 2026 federal student loan repayment math for AI agents. It covers RAP, IBR, ICR, PSLF and plan eligibility using Finology Software's parity-verified engine. Written in TypeScript.

Best for

Best for
Developers building AI agents that need accurate federal student loan repayment calculations

Use cases

  • Calculate monthly payments for income-driven repayment plans
  • Check eligibility for RAP, IBR, ICR, and PSLF
  • Embed deterministic loan math into AI agent tools

How to use

Tested with

Claude Desktop, Cursor

Example client config

{\n  "mcpServers": {\n    "finology": {\n      "command": "npx",\n      "args": ["-y", "@finology/mcp-server"]\n    }\n  }\n}

Notes

MCP server that provides deterministic 2026 federal student loan repayment math for AI agents. It covers RAP, IBR, ICR, PSLF and plan eligibility using Finology Software’s parity-verified engine. Written in TypeScript.

0 stars on GitHub. Last updated 2026-10-06. Licensed MIT.

Use cases

  • Calculate monthly payments for income-driven repayment plans
  • Check eligibility for RAP, IBR, ICR, and PSLF
  • Embed deterministic loan math into AI agent tools

Pros

  • Deterministic output for consistent agent decisions
  • Parity-verified engine for accuracy
  • TypeScript for type safety

Cons

  • No stars yet, so limited community validation
  • Tied to 2026 federal rules, may need updates
  • Designed for AI agents, not a general-purpose library

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

Pros

  • Deterministic output for consistent agent decisions
  • Parity-verified engine for accuracy
  • TypeScript for type safety

Cons

  • No stars yet, so limited community validation
  • Tied to 2026 federal rules, may need updates
  • Designed for AI agents, not a general-purpose library
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