Agent Registry

Overview

The Agnt Regstry MCP server serves as a central hub for organizing and discovering both Model Context Protocol (MCP) servers and Agent-to-Agent (A2A) agent cards. In many AI‑driven environments, developers must juggle dozens of distinct MCP endpoints—each exposing its own set of resources, tools, prompts, or sampling strategies. Agnt Regstry consolidates these endpoints into a single, searchable registry, allowing assistants to locate the most appropriate server or agent card at runtime without manual configuration.

At its core, Agnt Regstry exposes a lightweight MCP interface that lists available servers and agent cards. Clients can query the registry to retrieve metadata such as supported capabilities, version numbers, or authentication requirements. This discovery layer is especially valuable when an AI assistant needs to select a specialized tool (e.g., a language model fine‑tuned for legal text) from a pool of candidates. By offloading the lookup to the registry, developers avoid hard‑coding URLs or credentials into assistant prompts, thereby improving maintainability and security.

Key features include:

• Server cataloging: Each MCP server can be registered with a descriptive name, tags, and health‑check endpoints. The registry automatically monitors status and flags offline servers.
• Agent card management: A2A agent cards—self‑contained bundles of prompts, tools, and sampling logic—are stored as reusable artifacts. Assistants can pull a card from the registry to compose complex workflows on demand.
• Metadata enrichment: Servers and cards can be annotated with custom fields (e.g., cost per token, SLA guarantees) that assistants can use to make informed decisions.
• Access control: Fine‑grained permissions let administrators restrict visibility of certain servers or cards to specific teams or roles.

Typical use cases involve large‑scale AI platforms where multiple microservices expose MCP endpoints. A developer can register a new server or agent card with Agnt Regstry, and any assistant—regardless of its deployment location—will automatically discover it through the registry. This eliminates the need for manual propagation of configuration changes and reduces downtime caused by mis‑configured endpoints.

By integrating Agnt Regstry into an AI workflow, teams gain a dynamic, discoverable inventory of tools and agents. The registry becomes the single source of truth that enables assistants to compose sophisticated, context‑aware pipelines without manual intervention, ultimately accelerating development cycles and improving reliability across distributed AI systems.