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title, slug
| title | slug |
|---|---|
| Agents | /components-agents |
Agent components in Langflow
Agent components define the behavior and capabilities of AI agents in your flow.
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 an agent in a flow
The simple agent starter project uses an agent component connected to URL and Calculator tools to answer a user's questions. The OpenAI LLM acts as a brain for the agent to decide which tool to use. Tools are connected to agent components at the Tools port.
For a multi-agent example see Create a flow with an agent.
Agent component
This component creates an agent that can use tools to answer questions and perform tasks based on given instructions.
The component includes an LLM model integration, a system message prompt, and a Tools port to connect tools to extend its capabilities.
For more information on this component, see the Agent documentation.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| agent_llm | Dropdown | The provider of the language model that the agent uses to generate responses. Options include OpenAI and other providers or Custom. |
| system_prompt | String | The system prompt provides initial instructions and context to guide the agent's behavior. |
| tools | List | The list of tools available for the agent to use. This field is optional and can be empty. |
| input_value | String | The input task or question for the agent to process. |
| add_current_date_tool | Boolean | When true this adds a tool to the agent that returns the current date. |
| memory | Memory | An optional memory configuration for maintaining conversation history. |
| max_iterations | Integer | The maximum number of iterations the agent can perform. |
| handle_parsing_errors | Boolean | This determines whether to handle parsing errors during agent execution. |
| verbose | Boolean | This enables verbose output for detailed logging. |
Outputs
| Name | Type | Description |
|---|---|---|
| response | Message | The agent's response to the given input task. |
MCP tools
:::important Prior to Langflow 1.5, this component was named MCP connection. :::
The MCP tools component connects to a Model Context Protocol (MCP) server and exposes the MCP server's tools as tools for Langflow agents.
In addition to being an MCP client that can leverage MCP servers, the MCP tools component's SSE mode allows you to connect your flow to the Langflow MCP server at the /api/v1/mcp/sse API endpoint, exposing all flows within your project as tools within a flow.
For more information, see MCP client.
Legacy components
Legacy components are available for use but are no longer supported.
JSON Agent
This component creates a JSON agent from a JSON or YAML file and an LLM.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| path | File | The path to the JSON or YAML file. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The JSON agent instance. |
Vector Store Agent
This component creates a Vector Store Agent using LangChain.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| vectorstore | VectorStoreInfo | The vector store information for the agent to use. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The Vector Store Agent instance. |
Vector Store Router Agent
This component creates a Vector Store Router Agent using LangChain.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| vectorstores | List[VectorStoreInfo] | The list of vector store information for the agent to route between. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The Vector Store Router Agent instance. |