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sidclawhq/platform

by Various

The approval and accountability layer for agentic AI. Identity → Policy → Approval → Trace. Try: npx sidclaw-mcp-guard demo

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MCP

sidclawhq/platform

Added 1 June 2026

#agent-approval #agent-security #ai-agents #ai-governance #approval-workflow #audit-trail #claude-code #claude-code-hooks

Overview

The sidclawhq/platform is an open-source TypeScript library that implements an identity, policy, approval, and trace framework for agentic AI systems. It enforces an Identity → Policy → Approval → Trace pipeline to provide accountability and control over AI agent actions. Developers can test it via the command npx sidclaw-mcp-guard demo.

Best for

Best for
Developers building agentic AI systems that need governance, auditing, and approval controls.

Use cases

  • Auditing and tracing AI agent decision chains
  • Enforcing approval workflows before agent actions execute
  • Integrating identity-based policy checks into agent pipelines

Notes

The sidclawhq/platform is an open-source TypeScript library that implements an identity, policy, approval, and trace framework for agentic AI systems. It enforces an Identity → Policy → Approval → Trace pipeline to provide accountability and control over AI agent actions. Developers can test it via the command npx sidclaw-mcp-guard demo.

10 stars on GitHub. Last updated 2026-05-18. Licensed Apache-2.0.

Use cases

  • Auditing and tracing AI agent decision chains
  • Enforcing approval workflows before agent actions execute
  • Integrating identity-based policy checks into agent pipelines

Pros

  • Provides a structured governance layer for autonomous AI agents
  • Open source with a TypeScript codebase for easy integration
  • Enables traceability and accountability in agent workflows

Cons

  • Limited to 10 GitHub stars indicates early stage adoption
  • Requires embedding into existing agent infrastructure
  • Dependency on the npx demo command for initial evaluation

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

Pros

  • Provides a structured governance layer for autonomous AI agents
  • Open source with a TypeScript codebase for easy integration
  • Enables traceability and accountability in agent workflows

Cons

  • Limited to 10 GitHub stars indicates early stage adoption
  • Requires embedding into existing agent infrastructure
  • Dependency on the npx demo command for initial evaluation