add glossterms

Author: micheleRP

modules/ai-agents/pages/ai-gateway/admin/setup-guide.adoc

@@ -234,9 +234,9 @@ If a provider pool contains multiple providers, you can distribute traffic to ba
 
 == Configure MCP tools (optional)
 
-If your users will build AI agents that need access to tools via MCP (Model Context Protocol), configure MCP tool aggregation.
+If your users will build glossterm:AI agent[,AI agents] that need access to glossterm:MCP tool[,tools] via glossterm:MCP[,Model Context Protocol (MCP)], configure MCP tool aggregation.
 
-On the gateway details page, select the *MCP* tab to configure tool discovery and execution. The MCP proxy aggregates multiple MCP servers, allowing agents to find and call tools through a single endpoint.
+On the gateway details page, select the *MCP* tab to configure tool discovery and execution. The MCP proxy aggregates multiple glossterm:MCP server[,MCP servers], allowing agents to find and call tools through a single endpoint.
 
 === Add MCP servers
 

modules/ai-agents/pages/ai-gateway/builders/connect-your-agent.adoc

@@ -8,7 +8,7 @@
 
 include::ai-agents:partial$ai-gateway-byoc-note.adoc[]
 
-This guide shows you how to connect your AI agent or application to a Redpanda AI Gateway. This is also called "Bring Your Own Agent" (BYOA). You'll configure your client SDK, make your first request, and validate the integration.
+This guide shows you how to connect your glossterm:AI agent[] or application to a Redpanda AI Gateway. This is also called "Bring Your Own Agent" (BYOA). You'll configure your client SDK, make your first request, and validate the integration.
 
 After completing this guide, you will be able to:
 

modules/ai-agents/pages/ai-gateway/builders/discover-gateways.adoc

@@ -159,7 +159,7 @@ These limits help control costs and ensure fair resource allocation across teams
 
 === MCP Tools
 
-If MCP aggregation is enabled for your gateway, you can access tools from multiple MCP servers through a single endpoint.
+If glossterm:MCP[,Model Context Protocol (MCP)] aggregation is enabled for your gateway, you can access glossterm:MCP tool[,tools] from multiple glossterm:MCP server[,MCP servers] through a single endpoint.
 
 To discover available MCP tools:
 

modules/ai-agents/pages/ai-gateway/gateway-architecture.adoc

@@ -12,7 +12,7 @@ This page provides technical details about AI Gateway's architecture, request pr
 
 == Architecture overview
 
-AI Gateway consists of three planes: a control plane for configuration and management, a data plane for request processing and routing, and an observability plane for monitoring and analytics.
+AI Gateway consists of three planes: a glossterm:control plane[] for configuration and management, a glossterm:data plane[] for request processing and routing, and an observability plane for monitoring and analytics.
 
 // PLACEHOLDER: Add architecture diagram showing:
 // 1. Control Plane:

modules/ai-agents/pages/ai-gateway/gateway-quickstart.adoc

@@ -8,7 +8,7 @@
 
 include::ai-agents:partial$ai-gateway-byoc-note.adoc[]
 
-Redpanda AI Gateway provides unified access to multiple Large Language Model (LLM) providers and Model Context Protocol (MCP) servers through a single endpoint. This quickstart walks you through configuring your first gateway and routing requests through it.
+Redpanda AI Gateway provides unified access to multiple large language model (LLM) providers and glossterm:MCP[,Model Context Protocol (MCP)] servers through a single endpoint. This quickstart walks you through configuring your first gateway and routing requests through it.
 
 == Prerequisites
 
@@ -275,9 +275,9 @@ Monitor the fallback rate in observability to detect primary provider issues ear
 
 == Configure MCP tools (optional)
 
-If you're using AI agents, configure MCP (Model Context Protocol) tool aggregation.
+If you're using glossterm:AI agent[,AI agents], configure glossterm:MCP[,Model Context Protocol (MCP)] tool aggregation.
 
-On the Gateways page, select the *MCP* tab to configure tool discovery and execution. The MCP proxy aggregates multiple MCP servers behind a single endpoint, allowing agents to discover and call tools through the gateway.
+On the Gateways page, select the *MCP* tab to configure tool discovery and execution. The MCP proxy aggregates multiple glossterm:MCP server[,MCP servers] behind a single endpoint, allowing agents to discover and call glossterm:MCP tool[,tools] through the gateway.
 
 Configure the MCP settings:
 

modules/ai-agents/pages/ai-gateway/mcp-aggregation-guide.adoc

@@ -8,7 +8,7 @@
 
 include::ai-agents:partial$ai-gateway-byoc-note.adoc[]
 
-AI Gateway provides MCP (Model Context Protocol) aggregation, allowing AI agents to access tools from multiple MCP servers through a single unified endpoint. This eliminates the need for agents to manage multiple MCP connections and significantly reduces token costs through deferred tool loading.
+AI Gateway provides glossterm:MCP[,Model Context Protocol (MCP)] aggregation, allowing glossterm:AI agent[,AI agents] to access glossterm:MCP tool[,tools] from multiple glossterm:MCP server[,MCP servers] through a single unified endpoint. This eliminates the need for agents to manage multiple MCP connections and significantly reduces token costs through deferred tool loading.
 
 MCP aggregation benefits:
 
@@ -20,7 +20,7 @@ MCP aggregation benefits:
 
 == What is MCP?
 
-Model Context Protocol (MCP) is a standard for exposing tools (functions) that AI agents can discover and invoke. MCP servers provide tools like:
+glossterm:MCP[,Model Context Protocol (MCP)] is a standard for exposing tools (functions) that AI agents can discover and invoke. MCP servers provide tools like:
 
 * Database queries
 * File system operations

modules/ai-agents/pages/ai-gateway/what-is-ai-gateway.adoc

@@ -18,7 +18,7 @@ First, applications typically hardcode provider-specific SDKs. An application us
 
 Second, costs can spiral without visibility into usage patterns. Without a centralized view of token consumption across teams and applications, it's difficult to attribute costs to specific customers, features, or environments. Testing and debugging can generate unexpected bills, and there's no way to enforce budgets or rate limits per team or customer.
 
-Third, AI agents that use MCP (Model Context Protocol) servers face tool coordination challenges. Managing tool discovery and execution is repetitive across projects, and agents typically load all available tools upfront, which creates high token costs. There's also no centralized governance over which tools agents can access.
+Third, glossterm:AI agent[,AI agents] that use glossterm:MCP[,Model Context Protocol (MCP)] servers face tool coordination challenges. Managing tool discovery and execution is repetitive across projects, and agents typically load all available tools upfront, which creates high token costs. There's also no centralized governance over which tools agents can access.
 
 Finally, observability is fragmented across provider dashboards. You cannot reconstruct user sessions that span multiple models, compare latency and costs across providers in a unified view, or efficiently debug issues. Troubleshooting "the AI gave the wrong answer" requires manual log diving across different systems.
 
@@ -100,9 +100,9 @@ For reliability, you can configure provider pools with automatic failover. If yo
 
 === MCP aggregation and orchestration
 
-AI Gateway aggregates multiple MCP (Model Context Protocol) servers and provides deferred tool loading, which dramatically reduces token costs for AI agents.
+AI Gateway aggregates multiple glossterm:MCP server[,MCP servers] and provides deferred tool loading, which dramatically reduces token costs for AI agents.
 
-Without AI Gateway, agents typically load all available tools from multiple MCP servers at startup. This approach sends 50+ tool definitions with every request, creating high token costs (thousands of tokens per request), slow agent startup times, and no centralized governance over which tools agents can access.
+Without AI Gateway, agents typically load all available glossterm:MCP tool[,tools] from multiple MCP servers at startup. This approach sends 50+ tool definitions with every request, creating high token costs (thousands of tokens per request), slow agent startup times, and no centralized governance over which tools agents can access.
 
 With AI Gateway, you configure approved MCP servers once, and the gateway loads only search and orchestrator tools initially. Agents query for specific tools only when needed, which often reduces token usage by 80-90% depending on your configuration and the number of tools aggregated. You also gain centralized approval and governance over which MCP servers your agents can access.
 

modules/ai-agents/pages/mcp/remote/concepts.adoc

@@ -64,7 +64,8 @@ The `redpanda.otel_traces` topic has a predefined retention policy. Configuratio
 
 The topic persists in your cluster even after all MCP servers are deleted, allowing you to retain historical trace data for analysis.
 
-Trace data may contain sensitive information from your tool inputs and outputs. Consider implementing appropriate glossterm:ACL[,access control lists (ACLs)] for the `redpanda.otel_traces` topic, and review the data in traces before sharing or exporting to external systems.
+Trace data may contain sensitive information from your 
+tool inputs and outputs. Consider implementing appropriate glossterm:ACL[,access control lists (ACLs)] for the `redpanda.otel_traces` topic, and review the data in traces before sharing or exporting to external systems.
 
 === Understand the trace structure