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tardygrada
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tardygrada

Active·★ 16·MIT·Updated 2026-05-05
★ Trending★ Security & Safety★ LLM Infra

Trust infrastructure for AI agents. Know who produced a value, when, and that it hasn't been tampered with. Zero dependencies. Pure C.

Tardygrada is a programming language that compiles to MCP servers, where every value carries cryptographic proof of its creator, creation time, and integrity. It guarantees integrity via mprotect, SHA-256, ed25519, and BFT consensus (proven in Coq), provenance with signed metadata, and a full audit trail. However, it does not guarantee truth; it only ensures the value has not been changed, providing 100% proof even after 100 handoffs among agents.

#agent-framework#ai-agents#ai-safety#byzantine-fault-tolerance#c#coq#cryptography#ed25519
$ Install
$ git clone https://github.com/fabio-rovai/tardygrada && cd tardygrada && make
↗ Visit site★ GitHub
01

Features

01Integrity guarantees via OS kernel (mprotect) and cryptography (SHA-256, ed25519)
02Provenance tracking with signed metadata (who, when)
03Full audit trail for every operation
04Multiple immutability tiers (let, @verified, @hardened, @sovereign)
05Compiles to MCP servers for integration with agent frameworks
02

Compatibility

Linux
Linux (native)
Verified via docs
03

Quick start

1
$ git clone https://github.com/fabio-rovai/tardygrada
2
$ cd tardygrada
3
$ make
04

Use cases

↳Securing multi-agent systems where integrity of data passed between agents is critical
↳High-confidence domains like medical diagnosis requiring tamper-proof evidence
↳Retrofitting existing agent frameworks (CrewAI, LlamaIndex, MiroFish) with integrity proofs
05

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Related searches

tardygrada AlternativesBest Security & Safety Tools 2026Open Source Security & Safetytardygrada Tutorialtardygrada Vs Competitorsagent-frameworkai-agentsai-safety

Comments

Log in to leave a comment
  • Q
    Quinn WhiteMay 11, 2026

    Trust infrastructure for AI agents — provenance, timestamp, and integrity verification.

  • Kendall Lee
    Kendall LeeMay 7, 2026

    Works as a trust layer that other agent frameworks can build on.

  • E
    Ellis JohnsonApr 11, 2026

    Good for systems where knowing who produced a value and when is a requirement.

  • O
    Oakley RiveraMar 25, 2026

    Provenance tracking builds audit trails for AI-generated outputs.

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 16
Last commit3w ago
StatusActive
LicenseMIT
CategorySecurity & Safety
Trend (30d)
+0.6↑ 0.7%
Links
Documentation↗Discussion↗Issues↗Releases↗

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