Tool components in Langflow

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. For an example, see Make any component a tool.

arXiv

This component searches and retrieves papers from arXiv.org.

Inputs

Name	Display Name	Info
search_query	Search Query	The search query for arXiv papers (for example, quantum computing)
search_type	Search Field	The field to search in
max_results	Max Results	Maximum number of results to return

Outputs

Name	Display Name	Info
papers	Papers	List of retrieved arXiv papers

Astra DB Tool

The Astra DB Tool allows agents to connect to and query data from Astra DB collections.

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. Default: "*".
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.

Outputs

The Data output is primarily used when directly querying Astra DB, while the Tool output is used when integrating with LangChain agents or chains.

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.

The main difference between this tool and the Astra DB Tool is that this tool is specifically designed for CQL tables and requires partition keys for querying, while also supporting clustering keys for more specific queries.

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.

Inputs

Name	Type	Description
bing_subscription_key	SecretString	Bing API subscription key
input_value	String	Search query input
bing_search_url	String	Custom Bing Search URL (optional)
k	Integer	Number of search results to return

Outputs

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

Calculator Tool

This component creates a tool for performing basic arithmetic operations on a given expression.

Inputs

Name	Type	Description
expression	String	The arithmetic expression to evaluate (for example, 4*4*(33/22)+12-20).

Outputs

Name	Type	Description
result	Tool	Calculator tool for use in LangChain

This component allows you to evaluate basic arithmetic expressions. It supports addition, subtraction, multiplication, division, and exponentiation. The tool uses a secure evaluation method that prevents the execution of arbitrary Python code.

Combinatorial Reasoner

This component runs Icosa's Combinatorial Reasoning (CR) pipeline on an input to create an optimized prompt with embedded reasons. Sign up for access here: https://forms.gle/oWNv2NKjBNaqqvCx6

Inputs

Name	Display Name	Description
prompt	Prompt	Input to run CR on
openai_api_key	OpenAI API Key	OpenAI API key for authentication
username	Username	Username for Icosa API authentication
password	Password	Password for Icosa API authentication
model_name	Model Name	OpenAI LLM to use for reason generation

Outputs

Name	Display Name	Description
optimized_prompt	Optimized Prompt	A message object containing the optimized prompt
reasons	Selected Reasons	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.

Inputs

Name	Display Name	Info
input_value	Search Query	The search query to execute with DuckDuckGo.
max_results	Max Results	The maximum number of search results to return. Default: 5.
max_snippet_length	Max Snippet Length	The maximum length of each result snippet. Default: 100.

Outputs

Name	Display Name	Info
data	Data	List of search results as Data objects containing snippets and full content.
text	Text	Search results formatted as a single text string.

Exa Search

This component provides an [https://exa.ai/](Exa Search) toolkit for search and content retrieval.

Inputs

Name	Display Name	Info
metaphor_api_key	Exa Search API Key	API key for Exa Search (entered as a password)
use_autoprompt	Use Autoprompt	Whether to use autoprompt feature (default: true)
search_num_results	Search Number of Results	Number of results to return for search (default: 5)
similar_num_results	Similar Number of Results	Number of similar results to return (default: 5)

Outputs

Name	Display Name	Info
tools	Tools	List of search tools provided by the toolkit

Glean Search API

This component allows you to call the Glean Search API.

Inputs

Name	Type	Description
glean_api_url	String	URL of the Glean API
glean_access_token	SecretString	Access token for Glean API authentication
query	String	Search query input
page_size	Integer	Number of results per page (default: 10)
request_options	Dict	Additional options for the API request (optional)

Outputs

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

Google Search API

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component allows you to call the Google Search API.

Inputs

Name	Type	Description
google_api_key	SecretString	Google API key for authentication
google_cse_id	SecretString	Google Custom Search Engine ID
input_value	String	Search query input
k	Integer	Number of search results to return

Outputs

Name	Type	Description
results	List[Data]	List of search results
tool	Tool	Google Search tool for use in LangChain

Google Serper API

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

Inputs

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

Outputs

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

MCP server

This component connects to a Model Context Protocol (MCP) server and exposes the MCP server's tools as tools.

In addition to being an MCP client that can leverage MCP servers, Langflow is also an MCP server that exposes flows as tools through the /api/v1/mcp/sse API endpoint. For more information, see MCP integrations.

To use the MCP server component with an agent component, follow these steps:

1. Add the MCP server component to your workflow.
2. In the MCP server component, in the MCP Command field, enter the command to start your MCP server. For example, to start a Fetch server, the command is:

_10

uvx mcp-server-fetch

uvx is included with uv in the Langflow package. To use npx server commands, you must first install an LTS release of Node.js. For an example of starting npx MCP servers, see Connect an Astra DB MCP server to Langflow.

3. Click to get the server's list of Tools.
4. In the Tool field, select the server tool you want the component to use. The available fields change based on the selected tool. For information on the parameters, see the MCP server's documentation.
5. In the MCP server component, enable Tool mode. Connect the MCP server component's Toolset port to an Agent component's Tools port.

The flow looks similar to this:

6. Open the Playground. Ask the agent to summarize recent tech news. The agent calls the MCP server function fetch and returns the summary. This confirms the MCP server is connected, and its tools are being used in Langflow.

For more information, see MCP integrations.

MCP Server-Sent Events (SSE) mode

1. In the MCP Server component, select SSE. A default address appears in the MCP SSE URL field.
2. In the MCP SSE URL field, modify the default address to point at the SSE endpoint of the Langflow server you're currently running. The default value is http://localhost:7860/api/v1/mcp/sse.
3. In the MCP Server component, click to retrieve the server's list of Tools.
4. Click the Tools field. All of your flows are listed as tools.
5. Enable Tool Mode, and then connect the MCP Server component to an agent component's tool port. The flow looks like this:
6. Open the Playground and chat with your tool. The agent chooses the correct tool based on your query.

Inputs

Name	Type	Description
command	String	MCP command (default: uvx mcp-sse-shim@latest)

Outputs

Name	Type	Description
tools	List[Tool]	List of tools exposed by the MCP server

MCP Tools (stdio)

important

This component is deprecated as of Langflow version 1.3. Instead, use the MCP server component

MCP Tools (SSE)

important

This component is deprecated as of Langflow version 1.3. Instead, use the MCP server component

Python Code Structured Tool

This component creates a structured tool from Python code using a dataclass.

The component dynamically updates its configuration based on the provided Python code, allowing for custom function arguments and descriptions.

Inputs

Name	Type	Description
tool_code	String	Python code for the tool's dataclass
tool_name	String	Name of the tool
tool_description	String	Description of the tool
return_direct	Boolean	Whether to return the function output directly
tool_function	String	Selected function for the tool
global_variables	Dict	Global variables or data for the tool

Outputs

Name	Type	Description
result_tool	Tool │ Structured tool created from the Python code

Python REPL Tool

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component creates a Python REPL (Read-Eval-Print Loop) tool for executing Python code.

Inputs

Name	Type	Description
name	String	The name of the tool (default: "python_repl")
description	String	A description of the tool's functionality
global_imports	List[String]	List of modules to import globally (default: ["math"])

Outputs

Name	Type	Description
tool	Tool	Python REPL tool for use in LangChain

Retriever Tool

This component creates a tool for interacting with a retriever in LangChain.

Inputs

Name	Type	Description
retriever	BaseRetriever	The retriever to interact with
name	String	The name of the tool
description	String	A description of the tool's functionality

Outputs

Name	Type	Description
tool	Tool	Retriever tool for use in LangChain

SearXNG Search Tool

This component creates a tool for searching using SearXNG, a metasearch engine.

Inputs

Name	Type	Description
url	String	The URL of the SearXNG instance
max_results	Integer	Maximum number of results to return
categories	List[String]	Categories to search in
language	String	Language for the search results

Outputs

Name	Type	Description
result_tool	Tool	SearXNG search tool for use in LangChain

Search API

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component calls the searchapi.io API. It can be used to search the web for information.

For more information, see the SearchAPI documentation.

Inputs

Name	Display Name	Info
engine	Engine	The search engine to use (default: "google")
api_key	SearchAPI API Key	The API key for authenticating with SearchAPI
input_value	Input	The search query or input for the API call
search_params	Search parameters	Additional parameters for customizing the search

Outputs

Name	Display Name	Info
data	Search Results	List of Data objects containing search results
tool	Search API Tool	A Tool object for use in LangChain workflows

Serp Search API

This component creates a tool for searching using the Serp API.

Inputs

Name	Type	Description
serpapi_api_key	SecretString	API key for Serp API authentication
input_value	String	Search query input
search_params	Dict	Additional search parameters (optional)

Outputs

Name	Type	Description
results	List[Data]	List of search results
tool	Tool	Serp API search tool for use in LangChain

Tavily AI Search

This component performs searches using the Tavily AI search engine, which is optimized for LLMs and RAG applications.

Inputs

Name	Display Name	Info
api_key	Tavily API Key	Your Tavily API Key.
query	Search Query	The search query you want to execute with Tavily.
search_depth	Search Depth	The depth of the search.
topic	Search Topic	The category of the search.
max_results	Max Results	The maximum number of search results to return.
include_images	Include Images	Include a list of query-related images in the response.
include_answer	Include Answer	Include a short answer to original query.

Outputs

Name	Display Name	Info
data	Data	The search results as a list of Data objects.
text	Text	The search results formatted as a text string.

Wikidata

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component performs a search using the Wikidata API.

Inputs

Name	Display Name	Info
query	Query	The text query for similarity search on Wikidata.

Outputs

Name	Display Name	Info
data	Data	The search results from Wikidata API as a list of Data objects.
text	Message	The search results formatted as a text message.

Wikipedia API

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component creates a tool for searching and retrieving information from Wikipedia.

Inputs

Name	Type	Description
input_value	String	Search query input
lang	String	Language code for Wikipedia (default: "en")
k	Integer	Number of results to return
load_all_available_meta	Boolean	Whether to load all available metadata (advanced)
doc_content_chars_max	Integer	Maximum number of characters for document content (advanced)

Outputs

Name	Type	Description
results	List[Data]	List of Wikipedia search results
tool	Tool	Wikipedia search tool for use in LangChain

Wolfram Alpha API

This component creates a tool for querying the Wolfram Alpha API.

Inputs

Name	Type	Description
input_value	String	Query input for Wolfram Alpha
app_id	SecretString	Wolfram Alpha API App ID

Outputs

Name	Type	Description
results	List[Data]	List containing the Wolfram Alpha API response
tool	Tool	Wolfram Alpha API tool for use in LangChain

Yahoo Finance News Tool

This component creates a tool for retrieving news from Yahoo Finance.

Inputs

This component does not have any input parameters.

Outputs

Name	Type	Description
tool	Tool	Yahoo Finance News tool for use in LangChain