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Tools are typically connected to agent components at the Tools port. Agents use LLMs as a reasoning engine to decide which of the connected tool components to use to solve a problem. Tools in agentic functions are, essentially, functions that the agent can call to perform tasks or access external resources. A function is wrapped as a Tool object, with a common interface the agent understands. Agents become aware of tools through tool registration, where the agent is provided a list of available tools, typically at agent initialization. The Tool object’s description tells the agent what the tool can do. The agent then uses a connected LLM to reason through the problem to decide which tool is best for the job.

Use a tool in a flow

Tools are typically connected to agent components at the Tools port. The simple agent starter project uses URL and Calculator tools connected to an agent component to answer a user’s questions. The OpenAI LLM acts as a brain for the agent to decide which tool to use. Simple Agent(1) Pn To make a component into a tool that an agent can use, enable Tool Mode in the component. Enabling tool mode modifies a component input to accept calls from an agent. If the component you want to connect to an agent doesn’t have a Tool Mode option, you can modify the component’s inputs to become a tool.

arXiv

This component searches and retrieves papers from arXiv.org.
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Astra DB tool

This component allows agents to query data from Astra DB collections. To use this tool in a flow, connect it to an Agent component. The flow looks like this: Tool Astral DB Pn The Tool Name and Tool Description fields are required for the Agent to decide when to use the tool. Tool Name cannot contain spaces. The values for Collection Name, Astra DB Application Token, and Astra DB API Endpoint are found in your Astra DB deployment. For more information, see the DataStax documentation. In this example, an OpenAI embeddings component is connected to use the Astra DB tool component’s Semantic Search capability. To use Semantic Search, you must have an embedding model or Astra DB Vectorize enabled. If you try to run the flow without an embedding model, you will get an error. Open the Playground and ask a question about your data. The Agent uses the Astra DB Tool to return information about your collection.

Define Astra DB tool parameters

The Tool Parameters configuration pane allows you to define parameters for filter conditions for the component’s Find command. These filters become available as parameters that the LLM can use when calling the tool, with a better understanding of each parameter provided by the Description field.
  1. To define a parameter for your query, in the Tool Parameters pane, click Add a new row.
  2. Complete the fields based on your data. For example, with this filter, the LLM can filter by unique customer_id values.
  • Name: customer_id
  • Attribute Name: Leave empty if the attribute matches the field name in the database.
  • Description: "The unique identifier of the customer to filter by".
  • Is Metadata: False unless the value is stored in the metadata field.
  • Is Mandatory: True to require this filter.
  • Is Timestamp: False since the value is an ID, not a timestamp.
  • Operator: $eq to look for an exact match.
If you want to apply filters regardless of the LLM’s input, use the Static Filters option, which is available in the component’s Controls pane.
InputsOutputsThe Data output is used when directly querying Astra DB, while the Tool output is used when integrating with agents.

Astra DB CQL Tool

The Astra DB CQL Tool allows agents to query data from CQL tables in Astra DB.
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Bing Search API

This component allows you to call the Bing Search API.
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Combinatorial Reasoner

This component runs Icosa’s Combinatorial Reasoning (CR) pipeline on an input to create an optimized prompt with embedded reasons. For more information, see Icosa computing.
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This component performs web searches using the DuckDuckGo search engine with result-limiting capabilities.
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This component provides an Exa Search toolkit for search and content retrieval.
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Glean Search API

This component allows you to call the Glean Search API.
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Google Serper API

This component allows you to call the Serper.dev Google Search API.
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MCP connection

The MCP connection component exposes Model Context Protocol (MCP) servers, including your other flows, as tools for LLM Controls agents.MCP consists of parameters Such as :
  1. MODE: studio, sse
  2. MCP SSE URL: uvx mcp-server-fetch (example command)
  3. Tools

Wikidata

This component performs a search using the Wikidata API.
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Spreadsheet Query

This component provides tools for searching through spreadsheet data using SQL queries, natural language, filters, and aggregations. It also supports chart generation (line, scatter, bar, histogram, pie, box plots).
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Tool Calling Agent

This component is an agent designed to utilize various tools seamlessly within workflows. It uses a language model to process user input and decide which tools to call.
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Calculator

This component performs basic arithmetic operations on a given expression. It safely evaluates mathematical expressions using Python’s AST parser, supporting addition, subtraction, multiplication, division, and exponentiation.
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Python REPL

This component is a Python code executor that lets you run Python code with specific imported modules. Remember to always use print() to see your results.
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Search API

This component calls the searchapi.io API with result limiting. It returns organic search results with title, link, and snippet fields. Supports Google, Bing, and DuckDuckGo engines.
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Serp Search API

This component calls the Serp Search API with result limiting. It returns organic search results with title, link, and snippet fields.
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This component is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It supports configurable search depth, topic filtering, time ranges, and can include images and short answers.

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Wikipedia

This component calls the Wikipedia API to search and retrieve article content.
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NameDisplay NameInfo
input_valueInput
langLanguage
kNumber of results
load_all_available_metaLoad all available meta
doc_content_chars_maxDocument content characters max

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WolframAlpha API

This component enables queries to Wolfram Alpha for computational data, facts, and calculations across various topics, delivering structured responses.
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NameDisplay NameInfo
input_valueInput QueryExample query: ‘What is the population of France?‘
app_idApp ID

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Yahoo Finance

This component uses yfinance (unofficial package) to access financial data and market information from Yahoo Finance. It supports multiple data retrieval methods including stock info, news, balance sheets, earnings, and more.
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