mcp-gateway-registry
Eliminates tool sprawl and access control gaps by centralizing MCP servers behind enforced authentication and audit trails, reducing security risk and operat…
Enterprise-ready MCP Gateway & Registry that centralizes AI development tools with secure OAuth authentication, dynamic tool discovery, and unified access for both autonomous AI agents and AI coding assistants. Transform scattered MCP server chaos into governed, auditable tool access with Keycloak/Entra integration.
- Audit which AI agents accessed which tools and when for compliance reporting.
- Centralize scattered MCP servers behind one secure gateway with OAuth login.
- Discover available AI development tools dynamically without manual server registry updates.
Eliminates tool sprawl and access control gaps by centralizing MCP servers behind enforced authentication and audit trails, reducing security risk and operational overhead in AI agent deployments.
Enterprise teams managing multiple AI agents or coding assistants requiring centralized governance, compliance tracking, and credential management across development environments.
https://github.com/agentic-community/mcp-gateway-registry
By agentic-community
How to Get It
claude mcp add mcp-gateway-registry -- npx -y mcp-gateway-registry
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Help me audit which AI agents accessed which tools and when for compliance reporting
Trust Signals Auto-scanned
Data & Access
Community Pulse New
- MCP Gateway and Registry: Enterprise-Grade Tool Governance for AI Agents — Hacker News · 2 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 824 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 824 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.