mcp-gateway-registry
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.
No outside reports on file
This tool centralizes trust—it makes AI tool access easier but means one security problem can compromise many agents, so strong authentication, monitoring, and vetting of connected tools are essential.
Based on public adoption and transparency signals as of Oct 23, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachLocal or standard API callsLOW
- CredentialsRequires API key or tokenREVIEW
- Package sourceGitHub (agentic-community/mcp-gateway-registry)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
No npm or PyPI package is listed. Install from source: github.com/agentic-community/mcp-gateway-registry ↗
About MCP Gateway Registry
This is a central hub that collects AI development tools (called MCP servers) in one place, lets multiple AI agents and coding helpers use them, and controls access through login authentication. It handles tool discovery automatically and keeps a record of who used what.
Who it’s for
Teams building AI systems who need to share tools across multiple AI agents or assistants without letting each one access everything. Organizations that want security controls and audit trails around their AI tool usage.
Alternatives
- Anthropic's Model Context Protocol (MCP) tools: Direct MCP server connections without a central registry; simpler but less scalable. - LangChain Tool Manager: Open-source tool orchestration with fewer enterprise security features. - Custom API gateway (Kong, AWS API Gateway): General-purpose gateways that require more setup but offer flexibility.
Setup
Check these steps against the project’s own instructions before running anything.
Follow the project's README. The exact installation steps depend on your deployment setup (Docker, cloud platform, or local). The repository includes configuration examples for connecting to Keycloak or Entra ID for authentication.
Why this grade
Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 1k
- Listing last refreshed
- 2026-10-29
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Security reports
No reports found for this package in our research (last checked 2026-10-29).
Risks to watch for
- Access to all integrated tools: Once authenticated, the gateway can reach every MCP server connected to it, so compromised credentials expose all those tools. - Malicious tool definitions: A tool's description or code could trick the AI into harmful actions (like deleting data) by hiding instructions in tool names or parameters. - Credential theft: OAuth tokens and API keys stored in the registry could leak if the gateway is hacked or misconfigured. - Audit log exposure: Records of who accessed what might contain sensitive information about your AI's operations or reveal business logic. - Supply chain risk: If the gateway itself or its dependencies are compromised, every agent using it is affected.
How to lower the risk
Least-privilege permissions
- Give each AI agent only access to the specific tools it needs, not all available tools.
- Use separate OAuth credentials for different agents or use scopes to limit what each one can do.
Network isolation
- Run the gateway on a private network or require a VPN to access it from outside.
- Keep connected MCP servers on isolated networks and monitor traffic between them.
Monitoring
- Log every tool access and review logs regularly for unusual patterns (too many failures, off-hours activity, unexpected tools being called).
- Set up alerts if authentication fails repeatedly or if new tools are added without approval.
Red flags to watch for
- Tools with vague descriptions or unusual parameter names that could hide malicious intent.
- Any changes to the gateway software or connected tools that weren't approved by your team.
Questions
How do I install MCP Gateway Registry?
MCP Gateway Registry does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/agentic-community/mcp-gateway-registry.
Are there security reports about MCP Gateway Registry?
No reports found for this package in our research (last checked 2026-10-29). MCP Gateway Registry currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include access to all integrated tools.
Is MCP Gateway Registry actively maintained?
MCP Gateway Registry has 1k GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/agentic-community/mcp-gateway-registry before pinning it in production.
What are alternatives to MCP Gateway Registry?
Notable alternatives to MCP Gateway Registry include Anthropic's Model Context Protocol (MCP) tools (Direct MCP server connections without a central registry). You can also compare MCP Gateway Registry side by side with other skills in the Related tools section on this page.
Key facts
- Type
- AI agent skill
- Publisher
- agentic-community
- Source code
- github.com/agentic-community/mcp-gateway-registry
- Est. context load
- ~108 tokens idle · ~450 tokens when active (on-demand skill)
- Popularity
- 1k GitHub stars
- Last updated
- 2026-10-29
- Last graded
- 2026-10-23
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