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oerc-s/primordia

by Various

AI Agent Economic Settlement Infrastructure - Machine-to-Machine Clearing

O

MCP

oerc-s/primordia

Added 1 June 2026

Overview

An open-source TypeScript library providing infrastructure for machine-to-machine clearing and economic settlement between AI agents. It defines protocols and mechanisms for agents to transact and settle payments autonomously.

Best for

Best for
Developers building decentralized multi-agent systems that need automated settlement and clearing between autonomous agents.

Use cases

  • Building autonomous agent economies with built-in settlement
  • Implementing agent-to-agent payment and clearing systems
  • Creating multi-agent frameworks that require financial reconciliation

Notes

An open-source TypeScript library providing infrastructure for machine-to-machine clearing and economic settlement between AI agents. It defines protocols and mechanisms for agents to transact and settle payments autonomously.

0 stars on GitHub. Last updated 2026-01-31.

Use cases

  • Building autonomous agent economies with built-in settlement
  • Implementing agent-to-agent payment and clearing systems
  • Creating multi-agent frameworks that require financial reconciliation

Pros

  • Addresses a specific, emerging need for agent economic infrastructure
  • Open-source and written in TypeScript for broad compatibility
  • Lightweight and focuses purely on machine-to-machine clearing

Cons

  • Early-stage project with no stars and likely limited community adoption
  • May lack production hardening, documentation, or real-world testing
  • Unclear integration path with existing agent frameworks or blockchains

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

Pros

  • Addresses a specific, emerging need for agent economic infrastructure
  • Open-source and written in TypeScript for broad compatibility
  • Lightweight and focuses purely on machine-to-machine clearing

Cons

  • Early-stage project with no stars and likely limited community adoption
  • May lack production hardening, documentation, or real-world testing
  • Unclear integration path with existing agent frameworks or blockchains