{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"}],"enrichment":{"capability":"Connects MongoDB Atlas Vector Search to LangChain for semantic search and retrieval-augmented generation workflows using vector embeddings stored in MongoDB.","skillfed_tags":["vector-search","rag","mongodb"],"use_cases":["Build a RAG chatbot that retrieves context from MongoDB before generating answers with an LLM.","Implement semantic search over a large document corpus stored in MongoDB Atlas.","Integrate vector embeddings into an existing MongoDB-backed application without switching databases.","Prototype AI applications that combine LangChain orchestration with MongoDB vector storage.","Store and query embeddings from multiple embedding models in a single MongoDB collection."],"what_it_does":"langchain-mongodb is a LangChain integration that wraps MongoDB Atlas Vector Search, allowing you to use MongoDB as a vector store for semantic search and retrieval-augmented generation (RAG) applications. It depends on langchain, langchain-core, pymongo, and several text-processing libraries to handle embeddings, document storage, and similarity queries.\n\nThe package provides a MongoDBAtlasVectorSearch class that connects to a MongoDB Atlas cluster, stores vector embeddings in a collection, and retrieves documents by semantic similarity. You supply connection credentials, a database and collection name, a vector search index name, and an embedding model, then call methods like similarity_search() to find relevant documents. It is designed for workflows where you want to leverage MongoDB's native vector capabilities within a LangChain application.","worth_installing":"Yes, if you are already committed to MongoDB Atlas and LangChain for a RAG or semantic search application. The package has low install friction and no known vulnerabilities. However, the aging maintenance status (211 days since last release) and unclear license warrant verification before production use. Confirm license terms and compatibility with your LangChain version before deploying."},"id":"langchain-mongodb","links":{"html":"https://skillfed.io/packages/langchain-mongodb","md":"https://skillfed.io/packages/langchain-mongodb.md","pypi":"https://pypi.org/project/langchain-mongodb/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-15","license_spdx":null,"license_treatment":"unclear","name":"langchain-mongodb","python_support":"supports_current","summary":"An integration package connecting MongoDB and LangChain"},"popularity":{"monthly_downloads":1033318,"position":4465,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.11.0"}