LangChain Nodes Reference

This page provides a comprehensive overview of all LangChain nodes available in n8n. These nodes are part of the @n8n/nodes-langchain package.

Node Categories

Agents

Autonomous AI systems

Chains

Pre-built AI workflows

Tools

Agent capabilities

Memory

Conversation context

Vector Stores

Semantic search

Embeddings

Text vectorization

Language Models

LLM providers

Document Loaders

Data ingestion

Text Splitters

Text chunking

Agents

AI Agent

Node: @n8n/n8n-nodes-langchain.agent
Type: Root Node
Description: Main agent node for autonomous AI workflows Inputs:

Main (required)
Language Model (required)
Memory (optional)
Tools (optional, multiple)
Output Parser (optional)

Key Parameters:

promptType: auto, define, or guardrails
text: Custom prompt text
hasOutputParser: Enable structured output
needsFallback: Enable fallback model

Source Reference: /home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/agents/Agent/V3/AgentV3.node.ts:25

OpenAI Assistant

Node: @n8n/n8n-nodes-langchain.openAiAssistant
Type: Root Node
Description: Use OpenAI’s Assistant API with code interpreter and file search Features:

Code Interpreter
File Search
Function Calling
Persistent Threads

Chains

Chains are pre-built workflows for common AI tasks.

Basic LLM Chain

Node: @n8n/n8n-nodes-langchain.chainLlm
Description: Simple chain to prompt a language model Source Reference: /home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/chains/ChainLLM/ChainLlm.node.ts:23 Key Features:

Simple prompting interface
Optional output parsing
Batch processing support
Streaming responses

Parameters:

{
  promptType: 'auto' | 'define' | 'guardrails',
  text?: string,
  hasOutputParser?: boolean,
  batching: {
    batchSize: number,
    delayBetweenBatches: number
  }
}

Question and Answer Chain

Node: @n8n/n8n-nodes-langchain.chainRetrievalQa
Description: Answer questions about retrieved documents (RAG) Source Reference: /home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/chains/ChainRetrievalQA/ChainRetrievalQa.node.ts:20 Inputs:

Main (required)
Language Model (required)
Retriever (required)

Use Cases:

Document Q&A
Knowledge base search
RAG applications

Summarization Chain

Node: @n8n/n8n-nodes-langchain.chainSummarization
Description: Summarize long documents efficiently Methods:

Map-Reduce: Process chunks in parallel
Refine: Iteratively refine summary
Stuff: Single pass (for short docs)

Information Extractor

Node: @n8n/n8n-nodes-langchain.informationExtractor
Description: Extract structured data from unstructured text Features:

Define custom schema
Extract multiple entities
Handle large documents

Text Classifier

Node: @n8n/n8n-nodes-langchain.textClassifier
Description: Classify text into predefined categories Use Cases:

Content categorization
Intent detection
Topic classification

Sentiment Analysis

Node: @n8n/n8n-nodes-langchain.sentimentAnalysis
Description: Analyze sentiment in text Output:

Positive, Negative, or Neutral
Confidence score

Tools

Tools extend agent capabilities.

Calculator Tool

Node: @n8n/n8n-nodes-langchain.toolCalculator
Description: Perform mathematical calculations

Code Tool

Node: @n8n/n8n-nodes-langchain.toolCode
Description: Execute JavaScript or Python code Parameters:

language: javascript or python
code: Code to execute

HTTP Request Tool

Node: @n8n/n8n-nodes-langchain.toolHttpRequest
Description: Make HTTP requests to APIs Parameters:

method: GET, POST, PUT, DELETE, etc.
url: API endpoint
authentication: Auth method

Call n8n Sub-Workflow Tool

Node: @n8n/n8n-nodes-langchain.toolWorkflow
Description: Use another n8n workflow as a tool Source Reference: /home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/tools/ToolWorkflow/ToolWorkflow.node.ts:10

This is the most powerful tool - turn ANY n8n workflow into a tool your agent can use!

Parameters:

workflowId: Target workflow
description: Tool description for agent
inputs: Input schema

Vector Store Tool

Node: @n8n/n8n-nodes-langchain.toolVectorStore
Description: Query vector stores for semantic search Inputs:

Vector Store (required)

Wikipedia Tool

Node: @n8n/n8n-nodes-langchain.toolWikipedia
Description: Search Wikipedia

SerpAPI Tool

Node: @n8n/n8n-nodes-langchain.toolSerpApi
Description: Search Google using SerpAPI Requires: SerpAPI credentials

SearXng Tool

Node: @n8n/n8n-nodes-langchain.toolSearXng
Description: Privacy-focused meta search engine

Wolfram Alpha Tool

Node: @n8n/n8n-nodes-langchain.toolWolframAlpha
Description: Computational knowledge engine

Think Tool

Node: @n8n/n8n-nodes-langchain.toolThink
Description: Internal reasoning tool for agents

Memory

Memory nodes maintain conversation context.

Simple Memory

Node: @n8n/n8n-nodes-langchain.memoryBufferWindow
Description: In-memory conversation buffer Source Reference:

/home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/memory/MemoryBufferWindow/MemoryBufferWindow.node.ts:75

Parameters:

{
  sessionIdType: 'customKey' | 'expressionKey',
  sessionKey?: string,
  contextWindowLength: number // Number of messages to remember
}

Not suitable for production environments with Queue Mode or multi-main setups.

Redis Memory

Node: @n8n/n8n-nodes-langchain.memoryRedisChat
Description: Distributed memory using Redis Best for: Production with multiple workers

Postgres Memory

Node: @n8n/n8n-nodes-langchain.memoryPostgresChat
Description: SQL-based persistent memory Best for: Queryable conversation history

MongoDB Memory

Node: @n8n/n8n-nodes-langchain.memoryMongoDbChat
Description: Document-based memory storage

Xata Memory

Node: @n8n/n8n-nodes-langchain.memoryXata
Description: Xata database memory

Zep Memory

Node: @n8n/n8n-nodes-langchain.memoryZep
Description: Advanced memory with summarization and fact extraction Features:

Automatic summarization
Fact extraction
Long-term memory

Motorhead Memory

Node: @n8n/n8n-nodes-langchain.memoryMotorhead
Description: Motorhead memory service

Memory Manager

Node: @n8n/n8n-nodes-langchain.memoryManager
Description: Advanced memory management

Memory Chat Retriever

Node: @n8n/n8n-nodes-langchain.memoryChatRetriever
Description: Retrieve relevant past conversations

Language Models

OpenAI Models

Chat Model: @n8n/n8n-nodes-langchain.lmChatOpenAi
Completion Model: @n8n/n8n-nodes-langchain.lmOpenAi Supported Models:

GPT-4, GPT-4 Turbo
GPT-3.5 Turbo
Custom models via base URL

Anthropic (Claude)

Node: @n8n/n8n-nodes-langchain.lmChatAnthropic Models:

Claude 3 Opus
Claude 3 Sonnet
Claude 3 Haiku

Google Models

Gemini: @n8n/n8n-nodes-langchain.lmChatGoogleGemini
Vertex AI: @n8n/n8n-nodes-langchain.lmChatGoogleVertex

Azure OpenAI

Node: @n8n/n8n-nodes-langchain.lmChatAzureOpenAi

Cohere

Chat Model: @n8n/n8n-nodes-langchain.lmChatCohere
Completion Model: @n8n/n8n-nodes-langchain.lmCohere

Ollama (Local)

Chat Model: @n8n/n8n-nodes-langchain.lmChatOllama
Completion Model: @n8n/n8n-nodes-langchain.lmOllama Use Cases:

Local/private deployments
No API costs
Custom models

Other Providers

Groq: lmChatGroq - Fast inference
Mistral: lmChatMistralCloud
DeepSeek: lmChatDeepSeek
Hugging Face: lmOpenHuggingFaceInference
AWS Bedrock: lmChatAwsBedrock
OpenRouter: lmChatOpenRouter
Vercel AI Gateway: lmChatVercelAiGateway
X.AI (Grok): lmChatXAiGrok
Lemonade AI: lmChatLemonade

Retrievers

Retrievers fetch relevant documents for RAG applications.

Vector Store Retriever

Node: @n8n/n8n-nodes-langchain.retrieverVectorStore
Description: Retrieve documents from vector stores Source Reference:

/home/daytona/workspace/source/packages/@n8n/nodes-langchain/nodes/retrievers/RetrieverVectorStore/RetrieverVectorStore.node.ts:14

Parameters:

{
  topK: number // Number of results to return
}

Contextual Compression Retriever

Node: @n8n/n8n-nodes-langchain.retrieverContextualCompression
Description: Compress retrieved documents to relevant parts Uses: Reranker nodes to improve results

Multi-Query Retriever

Node: @n8n/n8n-nodes-langchain.retrieverMultiQuery
Description: Generate multiple queries for better retrieval

Workflow Retriever

Node: @n8n/n8n-nodes-langchain.retrieverWorkflow
Description: Use n8n workflow as a retriever

Document Loaders

Load data from various sources.

Default Data Loader

Node: @n8n/n8n-nodes-langchain.documentDefaultDataLoader
Description: Load text data from previous nodes

Binary Input Loader

Node: @n8n/n8n-nodes-langchain.documentBinaryInputLoader
Description: Load documents from binary files Supported Formats:

PDF
DOCX
TXT
CSV
JSON
HTML
Markdown

JSON Input Loader

Node: @n8n/n8n-nodes-langchain.documentJsonInputLoader
Description: Load structured JSON data

GitHub Loader

Node: @n8n/n8n-nodes-langchain.documentGithubLoader
Description: Load files from GitHub repositories

Text Splitters

Split documents into chunks for processing.

Character Text Splitter

Node: @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter
Description: Split by character count Parameters:

chunkSize: Characters per chunk
chunkOverlap: Overlap between chunks

Recursive Character Text Splitter

Node: @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter
Description: Smart splitting that preserves structure Recommended: Best for most use cases

Token Splitter

Node: @n8n/n8n-nodes-langchain.textSplitterTokenSplitter
Description: Split by token count Best for: Precise token budget management

Output Parsers

Structure LLM outputs.

Structured Output Parser

Node: @n8n/n8n-nodes-langchain.outputParserStructured
Description: Parse into custom JSON schema Example Schema:

{
  "type": "object",
  "properties": {
    "answer": { "type": "string" },
    "confidence": { "type": "number" }
  },
  "required": ["answer"]
}

Auto-fixing Output Parser

Node: @n8n/n8n-nodes-langchain.outputParserAutofixing
Description: Automatically fix malformed JSON

Item List Output Parser

Node: @n8n/n8n-nodes-langchain.outputParserItemList
Description: Extract lists from text

Rerankers

Improve search result quality.

Cohere Reranker

Node: @n8n/n8n-nodes-langchain.rerankerCohere
Description: Rerank search results using Cohere Use with: Contextual Compression Retriever

Triggers

Chat Trigger

Node: @n8n/n8n-nodes-langchain.chatTrigger
Description: Webhook-based chat interface Features:

REST API endpoint
Streaming responses
Session management

Manual Chat Trigger

Node: @n8n/n8n-nodes-langchain.manualChatTrigger
Description: Manual testing interface Best for: Development and testing

Utility Nodes

Model Selector

Node: @n8n/n8n-nodes-langchain.modelSelector
Description: Dynamically select language models

Tool Executor

Node: @n8n/n8n-nodes-langchain.toolExecutor
Description: Execute tools programmatically

Guardrails

Node: @n8n/n8n-nodes-langchain.guardrails
Description: Add safety checks and input validation Features:

Input validation
Output filtering
Safety checks
Custom rules

MCP (Model Context Protocol)

n8n supports MCP for advanced AI integrations:

MCP Client

Node: @n8n/n8n-nodes-langchain.mcpClient
Description: Connect to MCP servers

MCP Client Tool

Node: @n8n/n8n-nodes-langchain.mcpClientTool
Description: Use MCP as a tool

MCP Trigger

Node: @n8n/n8n-nodes-langchain.mcpTrigger
Description: Trigger workflows from MCP events

Vendor-Specific Nodes

OpenAI Node

Node: @n8n/n8n-nodes-langchain.openAi
Description: Direct OpenAI API access Operations:

Text generation
Image generation
Audio transcription
File operations

Anthropic Node

Node: @n8n/n8n-nodes-langchain.anthropic
Description: Direct Anthropic API access

Google Gemini Node

Node: @n8n/n8n-nodes-langchain.googleGemini
Description: Google Gemini operations

Ollama Node

Node: @n8n/n8n-nodes-langchain.ollama
Description: Ollama server operations

Next Steps

Build an Agent

Create your first AI agent

Vector Stores

Set up semantic search

Embeddings

Configure embedding models

Workflow Templates

Browse example workflows

Getting Started

Self-Hosting

Building Workflows

AI Workflows

Node Development

CLI Reference

​LangChain Nodes Reference

​Node Categories

Agents

Chains

Tools

Memory

Vector Stores

Embeddings

Language Models

Document Loaders

Text Splitters

​Agents

​AI Agent

​OpenAI Assistant

​Chains

​Basic LLM Chain

​Question and Answer Chain

​Summarization Chain

​Information Extractor

​Text Classifier

​Sentiment Analysis

​Tools

​Calculator Tool

​Code Tool

​HTTP Request Tool

​Call n8n Sub-Workflow Tool

​Vector Store Tool

​Wikipedia Tool

​SerpAPI Tool

​SearXng Tool

​Wolfram Alpha Tool

​Think Tool

​Memory

​Simple Memory

​Redis Memory

​Postgres Memory

​MongoDB Memory

​Xata Memory

​Zep Memory

​Motorhead Memory

​Memory Manager

​Memory Chat Retriever

​Language Models

​OpenAI Models

​Anthropic (Claude)

​Google Models

​Azure OpenAI

​Cohere

​Ollama (Local)

​Other Providers

​Retrievers

​Vector Store Retriever

​Contextual Compression Retriever

​Multi-Query Retriever

​Workflow Retriever

​Document Loaders

​Default Data Loader

​Binary Input Loader

​JSON Input Loader

​GitHub Loader

​Text Splitters

​Character Text Splitter

​Recursive Character Text Splitter

​Token Splitter

​Output Parsers

​Structured Output Parser

​Auto-fixing Output Parser

​Item List Output Parser

​Rerankers

​Cohere Reranker

​Triggers

​Chat Trigger

​Manual Chat Trigger

​Utility Nodes

LangChain Nodes Reference

Node Categories

Agents

AI Agent

OpenAI Assistant

Chains

Basic LLM Chain

Question and Answer Chain

Summarization Chain

Information Extractor

Text Classifier

Sentiment Analysis

Tools

Calculator Tool

Code Tool

HTTP Request Tool

Call n8n Sub-Workflow Tool

Vector Store Tool

Wikipedia Tool

SerpAPI Tool

SearXng Tool

Wolfram Alpha Tool

Think Tool

Memory

Simple Memory

Redis Memory

Postgres Memory

MongoDB Memory

Xata Memory

Zep Memory

Motorhead Memory

Memory Manager

Memory Chat Retriever

Language Models

OpenAI Models

Anthropic (Claude)

Google Models

Azure OpenAI

Cohere

Ollama (Local)

Other Providers

Retrievers

Vector Store Retriever

Contextual Compression Retriever

Multi-Query Retriever

Workflow Retriever

Document Loaders

Default Data Loader

Binary Input Loader

JSON Input Loader

GitHub Loader

Text Splitters

Character Text Splitter

Recursive Character Text Splitter

Token Splitter

Output Parsers

Structured Output Parser

Auto-fixing Output Parser

Item List Output Parser

Rerankers

Cohere Reranker

Triggers

Chat Trigger

Manual Chat Trigger

Utility Nodes

Model Selector

Tool Executor

Guardrails

MCP (Model Context Protocol)

MCP Client

MCP Client Tool

MCP Trigger

Vendor-Specific Nodes

OpenAI Node

Anthropic Node

Google Gemini Node

Ollama Node

Next Steps