Tool Binding
Also known as: Tool Registration, Tool Configuration
Definition
The process of connecting tool definitions to their implementations and making them available to an LLM or agent. Binding involves: defining the tool schema, implementing the execution logic, registering the tool with the application, and configuring any authentication or permissions. It's the bridge between "here's what this tool does" and "here's how to actually run it."
What this is NOT
- Not the tool definition alone (binding connects definition to implementation)
- Not tool execution (binding sets up tools; execution runs them)
- Not the model's decision to use a tool (that's tool selection)
Alternative Interpretations
Different communities use this term differently:
llm-practitioners
Configuring an agent framework (LangChain, LlamaIndex, etc.) with the tools it can use, including both the definitions sent to the model and the Python/JS functions that execute when tools are called.
Sources: LangChain Tool documentation, LlamaIndex tool usage, Agent framework documentation
Examples
- LangChain @tool decorator binding a Python function as a tool
- Registering MCP server tools with Claude Desktop
- Configuring OpenAI Assistants with file_search and code_interpreter tools
- Binding a database query function with authentication credentials
Counterexamples
Things that might seem like Tool Binding but are not:
- The tool definition in isolation (that's schema, not binding)
- The model outputting a tool call (that's invocation)
- The user deciding which tools to expose (that's configuration, pre-binding)
Relations
- requires tool-definition (Binding connects definitions to implementations)
- requires tool-use (Binding enables tool use)
- overlapsWith model-context-protocol (MCP standardizes how tools are bound and discovered)
Implementations
Tools and frameworks that implement this concept:
- Flowise secondary
- LangChain primary
- MCP Servers secondary
- Playwright MCP Server secondary
- Semantic Kernel primary