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João André Gomes Marques
João André Gomes Marques

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5 open source tools for AI agent governance in 2026

AI agents are moving into production faster than governance tooling can keep up. Here are the 5 open source tools worth knowing about.

1. Microsoft Agent Governance Toolkit

The 800-pound gorilla. Policy-as-code with Cedar, multi-language SDKs (Python, TypeScript, .NET, Rust, Go), 9,500+ tests. No cryptographic signing but the most mature policy engine.

github.com/microsoft/agent-governance-toolkit

2. asqav

Quantum-safe audit trails. Every agent action gets an ML-DSA-65 signature chained to the previous one. Works with LangChain, CrewAI, OpenAI Agents, Haystack, LiteLLM. The only tool with post-quantum signatures.

github.com/jagmarques/asqav-sdk

3. Guardrails AI

6.6K stars. Output validation and structural guarantees for LLM responses. Guardrails Hub has community validators. Different focus (output quality vs audit trails) but complementary.

github.com/guardrails-ai/guardrails

4. NeMo Guardrails

NVIDIA. Programmable conversation rails using Colang DSL. Topic control, safety rails, jailbreak prevention. Great for chatbot safety, less focused on agent audit trails.

github.com/NVIDIA/NeMo-Guardrails

5. AgentMint

Ed25519 signed receipts with zero dependencies. The init command auto-discovers tool calls in your codebase. Best developer experience for quick setup. No SaaS, fully local.

github.com/aniketh-maddipati/agentmint-python

When to use what

Regulated industry needing long-term proof: asqav (quantum-safe signatures hold up for 10+ years)

Enterprise policy enforcement: Microsoft AGT (most mature, multi-language)

LLM output quality: Guardrails AI

Conversation safety: NeMo Guardrails

Quick local receipts: AgentMint

Full comparison table: github.com/jagmarques/ai-agent-governance-landscape

Top comments (1)

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igorganapolsky profile image
Igor Ganapolsky

Great roundup. One tool worth adding to this landscape: ThumbGate (github.com/IgorGanapolsky/ThumbGate).

It fills a different niche than the tools listed here — it's specifically focused on pre-action gates for AI coding agents (Claude Code, Cursor, Copilot). Instead of auditing after the fact or validating outputs, it gates destructive operations before they execute.

The hard blocks vs soft steers distinction from your comparison table maps directly to our architecture: hard gates for file deletions and config overwrites, soft gates for less critical operations.

2,478 unique cloners in 14 days, MCP server included. Would be great to see it in the governance landscape comparison.