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24/06/2026 7:36 pm
TL;DR: AI agents can shift from hardcoded tool lists to runtime discovery, allowing them to find, select, and execute approved MCP servers as environments change, according to Kong. That improves flexibility, but it also makes tool governance, access boundaries, and registry trust the real control points for agentic systems.
NHIMG editorial — based on content published by Kong: Leveraging the MCP Registry in Kong Konnect for Dynamic Tool Discovery
Questions worth separating out
Q: How should security teams govern dynamic tool discovery for AI agents?
A: Security teams should treat tool discovery as a governed entitlement flow, not as a convenience feature.
Q: What breaks when AI agents discover tools at runtime instead of using hardcoded lists?
A: Hardcoded lists assume the tool set is stable enough to be embedded in code.
Q: How do you know if an MCP registry is being governed well?
A: A well-governed registry has clear ownership, environment scoping, and consistent metadata, and it only exposes capabilities that are approved for the agent’s operating context.
Practitioner guidance
- Define registry-level approval boundaries Separate development, staging, and production MCP registries so agents only discover tools appropriate to the environment they operate in.
- Bind tool metadata to ownership and purpose Require each registered MCP server to carry clear namespace, owner, execution context, and business purpose metadata before it can be exposed to agents.
- Review discovery queries as entitlement surfaces Test what an agent can discover before you test what it can execute, because search results can reveal capabilities that should remain hidden.
What's in the full article
Kong's full blog post covers the operational detail this post intentionally leaves for the source:
- Step-by-step examples of enabling MCP Registries in Konnect Labs and registering servers in the catalog
- The exact request and response flow for querying the registry API and selecting a matching MCP server
- Scenario walkthroughs showing how an agent behaves when no matching capability exists
- A concrete example of adding a new weather MCP server and activating it without changing agent code
👉 Read Kong's analysis of dynamic MCP tool discovery in Konnect →
MCP registry-driven discovery: what it means for IAM teams?
Explore further
25/06/2026 4:57 am
MCP registries are becoming identity control planes for agentic systems. The article shows that capability discovery is no longer a build-time concern. Once agents can query a registry at runtime, the registry becomes the gatekeeper for which tools exist, which environments they belong to, and which executions are legitimate. That is an identity problem as much as an integration problem. Practitioners should treat registry governance as part of agent entitlement management, not as adjacent platform plumbing.
A few things that frame the scale:
- 98% of companies plan to deploy even more AI agents within the next 12 months, despite documented rogue behaviour in 80% of current deployments, according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: What is the difference between tool registration and tool execution in agentic systems?
A: Tool registration makes a capability visible in the registry, while tool execution allows an agent to invoke it. Those controls should not be treated as the same thing. A tool can be registered for discoverability without being universally executable, which is essential for least-privilege agent governance.
👉 Read our full editorial: MCP registry-driven tool discovery changes agent governance
