Open Source

One Trusted Registry for Your Entire AI Stack

Package, curate, and deploy agents, MCP servers, skills, and LLMs from a single, governed registry. From curation to production in minutes.

Get Started
View Documentation

Azure AI Foundry

Kubernetes

CrewAI

Azure AI Foundry

Kubernetes

CrewAI

Full Lifecycle Management

From Import to Production

A complete workflow for managing AI artifacts across your organization.

Agentregistry Lifecycle flowAgentregistry Lifecycle flow
01
Catalog
02
Discovery
03
Runtime

Centralized registry for all AI artifacts

Catalog

Teams waste time rebuilding the same capabilities because they can’t find what already exists. A centralized catalog enables discovery, reuse, and consistency across multi-cloud environments.

Versioning
Semantic Search
Blueprints
Prompt Management
Multi-framework
Central Governance

Complete visibility across clouds

Discovery

Most organizations have tools and agents deployed across multiple clouds with no centralized visibility. Discovery eliminates blind spots with a complete inventory of your agent landscape.

Multi-cloud Discovery
Status
Shadow Inventory
Deployment Tracking
Drift Detection
Single Pane of Glass

Governance for running agents

Runtime

Without centralized runtime controls, teams face security gaps, cost overruns, and operational chaos. Runtime governance ensures agents run securely, efficiently, and within policy boundaries.

Multi-cloud Deployment
Centralized Observability
Access Policy
Context Optimization
Health Monitoring
RBAC
AWS Logo

AWS AgentCore

Databricks Logo

Databricks

LangSmith Logo

LangSmith

Kubernetes Logo

Kubernetes

Databricks Logo

Local Development

AWS Logo

AWS AgentCore

Databricks Logo

Databricks

LangSmith Logo

LangSmith

Kubernetes Logo

Kubernetes

Databricks Logo

Local Development

Freedom + control

Let Your AI Engineers Run Fast. And Safely.

Your AI teams should build what they want, how they want, and deploy where they want. Agentregistry gives developers the freedom to move at startup speed—while operators maintain full control over what's approved, secure, and production-ready.

Developer Velocity

One command to discover, pull, and deploy approved artifacts to any platform. No tickets, no waiting.

Operator Governance

Every artifact is curated, scored, and approved before it's available. Full audit trail included.

Platform Agnostic

Deploy to Kubernetes, cloud platforms, or local dev environments. Your choice, always.

Real-World Impact

Problems Solved, Teams Unblocked

From shadow AI chaos to governed velocity—agentregistry transforms how enterprises ship AI.

Platform Engineers

40 MCP servers. Zero visibility. Sound familiar?

Agents and MCP servers scattered across teams, registries, and laptops. Nobody knows what's tested, what's abandoned, or what has access to production data.

Agentregistry imports from any source, automatically scores and validates every artifact, and builds a searchable catalog your entire org can trust. Teams discover what exists before building from scratch.

Dialog box showing list of items:
"Auto-import from public registries, private repos, 
and existing deployments"
"Automatic scoring validates security, quality, and completeness on ingest"
"Semantic search surfaces existing artifacts before 
anyone rebuilds"
"Full audit trail — who created it, who approved it, 
where it's deployed"Dialog box showing list of items:
"Auto-import from public registries, private repos, 
and existing deployments"
"Automatic scoring validates security, quality, and completeness on ingest"
"Semantic search surfaces existing artifacts before 
anyone rebuilds"
"Full audit trail — who created it, who approved it, 
where it's deployed"

AI Developers

Weeks of setup for every new AI project? Not anymore.

Finding the right MCP server, vetting it for security, wiring it into your IDE, filing tickets to get it approved. The friction kills velocity.

One CLI. Pre-approved artifacts. Deploy to Cursor, VS Code, Claude Desktop, or Kubernetes in minutes. Agentregistry gets developers building instead of waiting.

Code box showing:
"$ arctl mcp list
  pokeapi-mcp-server   v1.2.0   ✓ published
  slack-mcp-server     v2.1.0   ✓ published
  github-mcp-server    v3.0.1   ✓ published

$ arctl mcp run slack-mcp-server
  ✓ Running on stdio

$ arctl configure cursor
  ✓ Cursor config updated"Code box showing:
"$ arctl mcp list
  pokeapi-mcp-server   v1.2.0   ✓ published
  slack-mcp-server     v2.1.0   ✓ published
  github-mcp-server    v3.0.1   ✓ published

$ arctl mcp run slack-mcp-server
  ✓ Running on stdio

$ arctl configure cursor
  ✓ Cursor config updated"

Security & Compliance

Three teams built the same agent. Two had critical security flaws.

Compliance asks which AI tools your teams are using. It takes two weeks of Slack threads and spreadsheets to piece together an incomplete answer. Meanwhile, unapproved agents are already in production.

Every artifact is versioned, scored, and published through a governed workflow. One validated version becomes the org standard. Compliance answers take seconds, not sprints.

100
%

Artifact visibility across your organization—who built it, who approved it, where it runs, every version change

Quickstart Guide
Join Discord

Discover more

Resources to help you succeed with agentregsitry.

Ready to take control of your AI infrastructure?

Join the community and start building with agentregistry today.

Star on GitHub
View Documentation