Chroma Docs llms.txt · AI Docs Browser · mdream [llms.txt Tools](https://mdream.dev/llms-txt/trychroma/llms-txt) # Chroma Docs llms.txt docs.trychroma.com/llms.txt [Raw llms.txt](https://docs.trychroma.com/llms.txt) [Raw llms-full.txt](https://docs.trychroma.com/llms-full.txt) Copy Markdown [](https://docs.trychroma.com/llms.txt) llms.txt Docs Fork collection Attach function Detach function Get attached function Collection Forking Chroma Cloud Package Search MCP Server Package Search Registry Pricing Quotas & Limits Index Configuration Reference Schema Overview Schema Basics Sparse Vector Search Setup Batch Operations Examples & Patterns Filtering with Where Group By & Aggregation Hybrid Search with RRF Migration Guide Search API Overview Pagination & Field Selection Ranking and Scoring Search Basics File Upload GitHub Overview S3 Sync Web Sync Browse Collections Copy Collections DB Management Installing the CLI Login Profile Management Run a Chroma Server Sample Apps Update Vacuum Adding Data to Chroma Collections Conditional Transactions Configure Collections Delete Data Manage Collections Update Data Embedding Functions Multimodal Embeddings Getting Started Introduction Migration Open Source Troubleshooting Full Text Search Metadata Filtering Query and Get Client-Server Mode Chroma Clients Agentic Memory Agentic Search Building with AI Chunking Intro to Retrieval Look at Your Data AWS Azure Running Chroma in Client-Server Mode Docker GCP Observability Chroma's Thin-Client Distributed/Cloud Performance General Single-Node Performance Integrations Amazon Bedrock Baseten Chroma BM25 Chroma Cloud Qwen Chroma Cloud Splade Cloudflare Workers AI Cohere Google Gemini Hugging Face Hugging Face Server Instructor Jina AI Mistral Morph Nomic Ollama OpenCLIP OpenAI Perplexity Roboflow Sentence Transformer Superlinked Text2Vec Together AI VoyageAI Anthropic MCP Braintrust Contextual AI DeepEval Google ADK Haystack Langchain LlamaIndex Mem0 OpenLIT OpenLLMetry Streamlit VoltAgent Distributed Architecture Architecture Overview Generate dense embeddings Generate sparse embeddings Kotlin Overview Client Collection Embedding Functions Schema Search Where Filters Rust Search Chroma Configuration Swift Upload and index a file Cancel invocation Create invocation Get invocation Get latest invocations by keys List invocations Create source Delete source Get source List sources Get service health status Client Collection Embedding Functions Schema Search Where Filters Where Filters OpenAPI Specs openapi sync.openapi ## What is Chroma Docs's llms.txt? Chroma Docs publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Chroma Docs offers and where to find details. Pass Spec 2 Sections 148 Links 17.7 KB Size ~4.5k Tokens Sections: Docs · OpenAPI Specs ## Add Chroma Docs Docs to Your AI Assistant Select your tool to see how to add Chroma Docs's llms.txt as a documentation source. Cursor Windsurf Claude Code ChatGPT Zed Copilot 1. 1 Open any chat or composer panel 2. 2 Type @Docs and select "Add new doc" 3. 3 Paste the URL: https://docs.trychroma.com/llms.txt 4. 4 Wait for the green dot (indexing complete) 5. 5 Reference @Docs in chat when asking about Chroma Docs Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too. ## Spec Compliance 3 notes ## Frequently Asked Questions Where is Chroma Docs's llms.txt file? Chroma Docs publishes its llms.txt at https://docs.trychroma.com/llms.txt. This file provides a structured, markdown-formatted index of Chroma Docs's documentation that AI systems can consume to understand the project's APIs, guides, and references. How do I use Chroma Docs's llms.txt with AI coding assistants? Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Chroma Docs's documentation so it can provide better code suggestions and answers about Chroma Docs. What does Chroma Docs's llms.txt contain? Chroma Docs's llms.txt contains 2 sections and 148 documentation links in 17.7 KB (~4.5k tokens). Key sections include Docs, OpenAPI Specs. How many tokens does Chroma Docs's llms.txt use? The concise llms.txt index is approximately 4.5k tokens (17.7 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline. Can I generate an llms.txt for my own project? Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator. ## Browse More llms.txt Files [Strapi Documentation](https://mdream.dev/llms-txt/trychroma/llms-txt/strapi) [Puck Puck is a modular, open-source visual editor for React.js. You can use Puck to build custom drag-and-drop experiences with your own application and React components. It's great for both internal page building applications or no-code page building products. Because Puck is just a React component, it plays well with all React.js environments, including Next.js. 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Validate your llms.txt against the official spec.](https://mdream.dev/llms-txt/trychroma/tools/llms-txt/validator) © 2026 [Harlan Wilton](https://github.com/harlan-zw) · [MIT](https://github.com/harlan-zw/mdream/blob/main/license) [GitHub](https://github.com/harlan-zw/mdream) [Discord](https://discord.com/invite/275MBUBvgP)