Tool components in LLM Controls

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.

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.

Parameters

Inputs

Name	Type	Description
search_query	String	The search query for arXiv papers. For example, `quantum computing`.
search_type	String	The field to search in.
max_results	Integer	The maximum number of results to return.

Outputs

Name	Type	Description
papers	List[Data]	A list of retrieved arXiv papers.

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:

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.

To define a parameter for your query, in the Tool Parameters pane, click Add a new row.
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.

Parameter	Description
Name	The name of the parameter that is exposed to the LLM. It can be the same as the underlying field name or a more descriptive label. The LLM uses this name, along with the description, to infer what value to provide during execution.
Attribute Name	When the parameter name shown to the LLM differs from the actual field or property in the database, use this setting to map the user-facing name to the correct attribute. For example, to apply a range filter to the timestamp field, define two separate parameters, such as `start_date` and `end_date`, that both reference the same timestamp attribute.
Description	Provides instructions to the LLM on how the parameter should be used. Clear and specific guidance helps the LLM provide valid input. For example, if a field such as `specialty` is stored in lowercase, the description should indicate that the input must be lowercase.
Is Metadata	When loading data using LangChain or LLM Controls, additional attributes may be stored under a metadata object. If the target attribute is stored this way, enable this option. It adjusts the query by generating a filter in the format: `{"metadata.<attribute_name>": "<value>"}`
Is Timestamp	For date or time-based filters, enable this option to automatically convert values to the timestamp format that the Astrapy client expects. This ensures compatibility with the underlying API without requiring manual formatting.
Operator	Defines the filtering logic applied to the attribute. You can use any valid Data API filter operator. For example, to filter a time range on the timestamp attribute, use two parameters: one with the `$gt` operator for “greater than”, and another with the `$lt` operator for “less than”.

Parameters

Inputs

Name	Type	Description
Tool Name	String	The name used to reference the tool in the agent’s prompt.
Tool Description	String	A brief description of the tool. This helps the model decide when to use it.
Collection Name	String	The name of the Astra DB collection to query.
Token	SecretString	The authentication token for accessing Astra DB.
API Endpoint	String	The Astra DB API endpoint.
Projection Fields	String	The attributes to return, separated by commas. The default is `*`.
Tool Parameters	Dict	Parameters the model needs to fill to execute the tool. For required parameters, use an exclamation mark, for example `!customer_id`.
Static Filters	Dict	Attribute-value pairs used to filter query results.
Limit	String	The number of documents to return.

OutputsThe Data output is used when directly querying Astra DB, while the Tool output is used when integrating with agents.

Name	Type	Description
Data	List[Data]	A list of Data objects containing the query results from Astra DB. Each `Data` object contains the document fields specified by the projection attributes. Limited by the `number_of_results` parameter.
Tool	StructuredTool	A LangChain `StructuredTool` object that can be used in agent workflows. Contains the tool name, description, argument schema based on tool parameters, and the query function.

Astra DB CQL Tool

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

Parameters

Inputs

Name	Type	Description
Tool Name	String	The name used to reference the tool in the agent’s prompt.
Tool Description	String	A brief description of the tool to guide the model in using it.
Keyspace	String	The name of the keyspace.
Table Name	String	The name of the Astra DB CQL table to query.
Token	SecretString	The authentication token for Astra DB.
API Endpoint	String	The Astra DB API endpoint.
Projection Fields	String	The attributes to return, separated by commas. Default: ”*”.
Partition Keys	Dict	Required parameters that the model must fill to query the tool.
Clustering Keys	Dict	Optional parameters the model can fill to refine the query. Required parameters should be marked with an exclamation mark, for example, `!customer_id`.
Static Filters	Dict	Attribute-value pairs used to filter query results.
Limit	String	The number of records to return.

Outputs

Name	Type	Description
Data	List[Data]	A list of Data objects containing the query results from the Astra DB CQL table. Each Data object contains the document fields specified by the projection fields. Limited by the `number_of_results` parameter.
Tool	StructuredTool	A LangChain StructuredTool object that can be used in agent workflows. Contains the tool name, description, argument schema based on partition and clustering keys, and the query function.

Bing Search API

This component allows you to call the Bing Search API.

Parameters

Inputs

Name	Type	Description
bing_subscription_key	SecretString	A Bing API subscription key.
input_value	String	The search query input.
bing_search_url	String	A custom Bing Search URL.
k	Integer	The number of search results to return.

Outputs

Name	Type	Description
results	List[Data]	A list of search results.
tool	Tool	A Bing Search tool for use in LangChain.

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.

Parameters

Inputs

Name	Type	Description
prompt	String	The input to run CR on.
openai_api_key	SecretString	An OpenAI API key for authentication.
username	String	A username for Icosa API authentication.
password	SecretString	A password for Icosa API authentication.
model_name	String	The OpenAI LLM to use for reason generation.

Outputs

Name	Type	Description
optimized_prompt	Message	A message object containing the optimized prompt.
reasons	List[String]	A list of the selected reasons that are embedded in the optimized prompt.

DuckDuckGo search

This component performs web searches using the DuckDuckGo search engine with result-limiting capabilities.

Parameters

Inputs

Name	Type	Description
input_value	String	The search query to execute with DuckDuckGo.
max_results	Integer	The maximum number of search results to return. Default: 5.
max_snippet_length	Integer	The maximum length of each result snippet. Default: 100.

Outputs

Name	Type	Description
data	List[Data]	A list of search results as Data objects containing snippets and full content.
text	String	The search results formatted as a single text string.

Exa Search

This component provides an Exa Search toolkit for search and content retrieval.

Parameters

Inputs

Name	Type	Description
metaphor_api_key	SecretString	An API key for Exa Search.
use_autoprompt	Boolean	Whether to use the autoprompt feature. Default: true.
search_num_results	Integer	The number of results to return for search. Default: 5.
similar_num_results	Integer	The number of similar results to return. Default: 5.

Outputs

Name	Type	Description
tools	List[Tool]	A list of search tools provided by the toolkit.

Glean Search API

This component allows you to call the Glean Search API.

Parameters

Inputs

Name	Type	Description
glean_api_url	String	The URL of the Glean API.
glean_access_token	SecretString	An access token for Glean API authentication.
query	String	The search query input.
page_size	Integer	The number of results per page. Default: 10.
request_options	Dict	Additional options for the API request.

Outputs

Name	Type	Description
results	List[Data]	A list of search results.
tool	Tool	A Glean Search tool for use in LangChain.

Google Serper API

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

Parameters

Inputs

Name	Type	Description
serper_api_key	SecretString	An API key for Serper.dev authentication.
input_value	String	The search query input.
k	Integer	The number of search results to return.

Outputs

Name	Type	Description
results	List[Data]	A list of search results.
tool	Tool	A Google Serper search tool for use in LangChain.

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 :

Parameters

MODE: studio, sse
MCP SSE URL: uvx mcp-server-fetch (example command)
Tools

Wikidata

This component performs a search using the Wikidata API.

Parameters

Inputs

Name	Type	Description
query	String	The text query for similarity search on Wikidata.

Outputs

Name	Type	Description
data	List[Data]	The search results from Wikidata API as a list of Data objects.
text	Message	The search results formatted as a text message.

Welcome

Get started

Templates

Concepts

Components

Integrations

Tool components in LLM Controls

Use a tool in a flow

arXiv

Astra DB tool

Define Astra DB tool parameters

Astra DB CQL Tool

Bing Search API

Combinatorial Reasoner

DuckDuckGo search

Exa Search

Glean Search API

Google Serper API

MCP connection

Wikidata

Welcome

Get started

Templates

Concepts

Components

Integrations

​Use a tool in a flow

​arXiv

​Astra DB tool

​Define Astra DB tool parameters

​Astra DB CQL Tool

​Bing Search API

​

​Combinatorial Reasoner

​

​DuckDuckGo search

​Exa Search

​

​Glean Search API

​

​Google Serper API

​

​MCP connection

​Wikidata

Use a tool in a flow

arXiv

Astra DB tool

Define Astra DB tool parameters

Astra DB CQL Tool

Bing Search API

Combinatorial Reasoner

DuckDuckGo search

Exa Search

Glean Search API

Google Serper API

MCP connection

Wikidata