Sign up for LlamaCloud today — get started with 10k free credits!
LlamaIndex

LlamaIndex 2025-07-08

LlamaIndex Newsletter 2025-07-08

Hi there, Llama Lovers! 🦙

Welcome to this week's edition of the LlamaIndex newsletter! We're excited to bring you major updates including the launch of NotebookLlama (our open-source NotebookLM alternative), the standalone release of Workflows 1.0, comprehensive context engineering insights, and powerful new MCP integrations. Plus, we've got exciting developments in LlamaExtract with automatic schema generation and enhanced enterprise RAG scaling capabilities.

🤩 The Highlights:

  • NotebookLlama Launch: We've built an open-source alternative to NotebookLM that runs entirely on your computer! Built on LlamaCloud with best-in-class parsing, it provides document chat, summaries, Q&A, mind maps, and podcast-like audio conversations. GitHub Repo, LlamaCloud, Documentation.
  • Context Engineering Deep Dive: Moving beyond prompt engineering to focus on filling LLM context windows with the most relevant information. Learn techniques for smart knowledge base selection, strategic memory storage, and structured information extraction. Read the full guide.
  • Workflows 1.0 Standalone Release: Our lightweight orchestration framework is now independent with dedicated Python and TypeScript packages, typed workflow state, resource injection, and built-in observability support. Get started.

🗺️ LlamaCloud And LlamaParse:

  • Automatic Schema Generation in LlamaExtract: New feature that automatically generates schemas from documents and prompts, removing the friction of manual schema building. Just provide a document and describe what you want! Try LlamaExtract, Learn more.
  • Enterprise RAG Scaling Insights: Learn from our experience scaling LlamaCloud for enterprise workloads, including handling noisy neighbor problems, access control complexity, document parsing challenges, and failure planning. Read the blog post.
  • Multi-modal Image Retrieval: You can now retrieve images and illustrative figures from your LlamaCloud Indexes alongside text by simply toggling "Multi-modal indexing" on your Index. Example notebook, Documentation.
  • Structured Data Extraction Workflow: Complete workflow with human-in-the-loop validation for data extraction using LlamaParse, OpenAI for JSON schema generation, and LlamaExtract for reliable extraction. Implementation guide.

✨ Framework:

  • Native LlamaCloud MCP Server: Connect your LlamaCloud projects directly to MCP clients like Claude Desktop for instant access to private data and LlamaExtract agents. GitHub repo.
  • Agent Memory Implementation: Comprehensive guide to building memory-aware agents with both short-term memory buffers and long-term memory using vector, fact, and custom-built blocks. Watch the recording.
  • Anthropic Tool Calling with Citations: Build citable AI applications using Anthropic's server-side tool calling with automatic citations and source attribution. Documentation.
  • MCP Tool Conversion: Transform any LlamaIndex agent tool into an MCP tool in just a few lines of code, with examples using the Notion Tool. Implementation guide, Available tools.

✍️ Community:

  • AI Hack Night at GitHub: Join us for a hands-on event in San Francisco with lightning talks from leading AI companies and 2.5 hours to build cutting-edge applications with AI Agents, MCPs, and RAG. Event details.
  • MCP Office Hours: Join our Discord for office hours (just a couple of hours from now!) focused on LlamaCloud MCP servers, using MCP tools with Agent Workflows, and extending open-source MCP servers. Register, LlamaIndex Calendar.
  • RAG Evaluation with DeepEval: Guest post showing how to build better RAG applications by combining LlamaIndex with comprehensive evaluation using Answer Relevancy, Faithfulness, and Contextual Precision metrics. Read the tutorial.
  • NASA Space Explorer Assistant: Winner of the Gradio MCP Hackathon, built with 3 MCP servers and 15 tools using NASA APIs for astronomy pictures, Mars Rover data, and asteroid information, orchestrated with a LlamaIndex FunctionAgent.