What Is a Tool Registry?
A tool registry is a structured catalog that defines all the tools available to an AI agent or multi-agent system. It stores each tool's name, description, input schema, and invocation details — everything the agent needs to understand what a tool does and how to call it.
In a simple agent, the tool registry is just a static list of function definitions passed to the LLM at initialization. In more sophisticated systems, it is a dynamic service that agents can query to discover capabilities at runtime, filter by category, or even register new tools programmatically.
Why a Tool Registry Matters
An agent cannot use a tool it does not know exists. The registry solves the discovery problem:
- For the LLM — Tool descriptions and schemas in the registry are what the model uses to decide when and how to call a tool. Poorly written registry entries lead to incorrect or missed tool usage.
- For the runtime — The registry maps tool names to executable functions, so when the model requests a call, the scaffold knows where to route it.
- For multi-agent systems — A shared registry allows multiple agents to discover and use the same tools without each agent needing its own hardcoded list.
- For governance — A centralized registry makes it easy to add, remove, or update tools system-wide without changing individual agents.
What a Tool Registry Entry Contains
A well-structured registry entry includes:
- Name — A unique, descriptive identifier (e.g.,
extract_url,search_knowledge). - Description — A clear natural-language explanation of what the tool does and when to use it. This is what the LLM reads to make decisions.
- Input schema — A JSON Schema definition of the tool's parameters: types, required fields, and descriptions of each field.
- Output format — A description of what the tool returns, so the model can reason about the result.
- Invocation details — The actual function or API endpoint to call (not exposed to the LLM, only to the runtime).
Example Registry Entry
{
"name": "extract_url",
"description": "Extracts structured knowledge from a webpage URL. Use this when you need product details, pricing, company information, or any structured data from a specific web page.",
"parameters": {
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "The full URL of the page to extract."
}
},
"required": ["url"]
}
}
This entry corresponds to KnowledgeSDK's /v1/extract endpoint. The description tells the agent when to use it; the schema tells the agent what to pass.
Dynamic vs. Static Registries
- Static registry — Tool list is hardcoded at agent initialization. Simple and fast; appropriate for most applications.
- Dynamic registry — Tools can be added, removed, or updated at runtime. Useful when the set of available capabilities changes frequently or when agents need to discover tools they were not initialized with.
Tool Registries and MCP
The Model Context Protocol standardizes the tool registry concept across applications. An MCP server's tools/list endpoint is effectively a dynamic tool registry: any MCP-compatible agent can query it to discover available tools, their schemas, and their descriptions — without any application-specific configuration.
KnowledgeSDK's @knowledgesdk/mcp package exposes a complete MCP-compliant tool registry covering all KnowledgeSDK capabilities, making them available to any MCP-aware agent or IDE with no custom integration code required.