langchain-dependencies

$22

langchain-ai/langchain-skills|Updated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGoose

Installation Guide

Select your AI agent

How to use langchain-dependencies on Cursor

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Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add langchain-dependencies

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/langchain-ai/langchain-skills --skill langchain-dependencies

Fetches langchain-dependencies from langchain-ai/langchain-skills and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/langchain-dependencies

Restart Cursor to activate langchain-dependencies. Access via /langchain-dependencies in your agent's command palette.

⚠

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Requirement	Python	TypeScript / Node
Runtime minimum	Python 3.10+	Node.js 20+
LangChain	1.0+ (LTS)	1.0+ (LTS)
LangSmith SDK	>= 0.3.0	>= 0.3.0

Framework	When to use	Core extra package
LangGraph	Need fine-grained graph control, custom workflows, loops, or branching	`langgraph` / `@langchain/langgraph`
Deep Agents	Want batteries-included planning, memory, file context, and skills out of the box	`deepagents` (depends on LangGraph; installs it as a transitive dep)

Package	Role	Min version
`langchain`	Agents, chains, retrieval	1.0
`langchain-core`	Base types & interfaces (peer dep)	1.0
`langsmith`	Tracing, evaluation, datasets	0.3.0

Package	Use when	Min version
`langgraph`	Building custom graphs directly	1.0
`deepagents`	Using the Deep Agents framework	latest

Package	Provider
`langchain-openai`	OpenAI (GPT-4o, o3, …)
`langchain-anthropic`	Anthropic (Claude)
`langchain-google-genai`	Google (Gemini)
`langchain-mistralai`	Mistral
`langchain-groq`	Groq (fast inference)
`langchain-cohere`	Cohere
`langchain-fireworks`	Fireworks AI
`langchain-together`	Together AI
`langchain-huggingface`	Hugging Face Hub
`langchain-ollama`	Ollama (local models)
`langchain-aws`	AWS Bedrock
`langchain-azure-ai`	Azure AI Foundry

Package	Adds	Notes
`langchain-tavily`	Tavily web search (`TavilySearch`)	Dedicated integration package; prefer latest
`langchain-text-splitters`	Text chunking utilities	Semver, keep current
`langchain-community`	1000+ integrations (fallback)	NOT semver — pin to minor series
`faiss-cpu`	FAISS vector store (local)	Via `langchain-community`; use latest
`langchain-chroma`	Chroma vector store	Dedicated integration package; prefer latest
`langchain-pinecone`	Pinecone vector store	Dedicated integration package; prefer latest
`langchain-qdrant`	Qdrant vector store	Dedicated integration package; prefer latest
`langchain-weaviate`	Weaviate vector store	Dedicated integration package; prefer latest
`langsmith[pytest]`	pytest plugin for LangSmith	Requires langsmith >= 0.3.4

Package	Role	Min version
`@langchain/core`	Base types & interfaces (peer dep)	1.0
`langchain`	Agents, chains, retrieval	1.0
`langsmith`	Tracing, evaluation, datasets	0.3.0

Package	Use when	Min version
`@langchain/langgraph`	Building custom graphs directly	1.0
`deepagents`	Using the Deep Agents framework	latest

Package	Provider
`@langchain/openai`	OpenAI (GPT-4o, o3, …)
`@langchain/anthropic`	Anthropic (Claude)
`@langchain/google-genai`	Google (Gemini)
`@langchain/mistralai`	Mistral
`@langchain/groq`	Groq (fast inference)
`@langchain/cohere`	Cohere
`@langchain/aws`	AWS Bedrock
`@langchain/azure-openai`	Azure OpenAI
`@langchain/ollama`	Ollama (local models)

Package	Adds	Notes
`@langchain/tavily`	Tavily web search (`TavilySearch`)	Dedicated integration package; prefer latest
`@langchain/community`	Broad set of community integrations	Use sparingly; prefer dedicated packages
`@langchain/pinecone`	Pinecone vector store	Dedicated integration package; prefer latest
`@langchain/qdrant`	Qdrant vector store	Dedicated integration package; prefer latest
`@langchain/weaviate`	Weaviate vector store	Dedicated integration package; prefer latest

Package group	Versioning	Safe upgrade strategy
`langchain`, `langchain-core`	Strict semver (1.0 LTS)	Allow minor: `>=1.0,<2.0`
`langgraph` / `@langchain/langgraph`	Strict semver (v1 LTS)	Allow minor: `>=1.0,<2.0`
`langsmith`	Strict semver	Allow minor: `>=0.3.0`
Dedicated integration packages (e.g. `langchain-tavily`, `langchain-chroma`)	Independently versioned	Allow minor updates; use latest
`langchain-community`	NOT semver	Pin exact minor: `>=0.4.0,<0.5.0`
`deepagents`	Follow project releases	Pin to tested version in production

langchain-dependencies

Installation Guide

How to use langchain-dependencies on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

Environment Requirements

Framework Choice

Core Packages

Python — always required

Python — orchestration (pick one)

Python — model providers (pick the one(s) you use)

Python — common tool & retrieval packages

TypeScript — always required

TypeScript — orchestration (pick one)

TypeScript — model providers (pick the one(s) you use)

TypeScript — common tool & retrieval packages

Minimal Project Templates

Add your model provider, e.g.:

langchain-openai

langchain-anthropic

langchain-google-genai

Add your model provider, e.g.:

langchain-anthropic

langchain-openai

Web search

Vector store — pick one:

langchain-pinecone # use latest; partner package, semver

langchain-qdrant # use latest; partner package, semver

Text processing

Your model provider:

langchain-openai / langchain-anthropic / etc.

Versioning Policy & Upgrade Strategy

Environment Variables

Common Mistakes

CORRECT: LangChain 1.0 LTS

WRONG: allows minor-version updates that may be breaking

CORRECT: pin to exact minor series

RISKY: old pin may be incompatible with LangChain 1.0

BETTER: allow latest within the current major

Implementation Guide

Best Practices

When to Use This

Learning Path

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Reviews

Discussion