aid: chroma name: Chroma kind: company description: >- Chroma (Chroma DB) is an open-source AI-native embedding database designed to make it easy to build LLM applications by providing storage, retrieval, and management for vector embeddings, full-text search, regex search, and multi-modal retrieval (text, image, audio). Distributed under the Apache 2.0 license, Chroma can be self-hosted (single-node Python or distributed Rust-based deployment) or consumed via Chroma Cloud, a managed serverless vector database service offering usage-based pricing. Chroma is the open-source data infrastructure for AI agents and RAG (Retrieval-Augmented Generation) applications, with first-party SDKs for Python and JavaScript/TypeScript and integrations with leading embedding providers (OpenAI, Cohere, Hugging Face, sentence-transformers). url: https://raw.githubusercontent.com/api-evangelist/chroma/refs/heads/main/apis.yml type: Index position: Consumer access: 3rd-Party image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg tags: - AI - AI Native - Apache 2.0 - Cloud - Embeddings - Hybrid Search - JavaScript - LLM - Machine Learning - Multi-Modal - Open Source - Python - RAG - Retrieval - SDK - Search - Serverless - TypeScript - Vector Database created: '2025-03-07' modified: '2026-05-19' specificationVersion: '0.20' apis: - aid: chroma:server-api name: Chroma Server API description: >- The Chroma Server API is a REST API that provides access to the Chroma open-source vector database. It enables developers to create and manage collections of embeddings, add documents with automatic tokenization and embedding, and perform vector similarity searches. The API supports metadata filtering, full-text search, and collection management operations. An OpenAPI specification is available at the server endpoint for client generation in various programming languages. image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.trychroma.com humanURL: https://docs.trychroma.com/reference/chroma-reference tags: - AI - Embeddings - Machine Learning - Search - Vector Database properties: - type: Documentation url: https://docs.trychroma.com/reference/chroma-reference - type: OpenAPI url: openapi/chroma-server-api-openapi.yml - aid: chroma:cloud-api name: Chroma Cloud API description: >- Chroma Cloud is a managed, serverless vector database service that provides fast and scalable vector, full-text, and metadata search across terabytes of data. It is backed by Chroma's Apache 2.0 distributed database and offers usage-based pricing with starter and team plans. Developers can connect to Chroma Cloud using the Python or JavaScript client SDKs without needing to manage infrastructure. image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg baseURL: https://api.trychroma.com humanURL: https://docs.trychroma.com/cloud/pricing tags: - AI - Cloud - Embeddings - Serverless - Vector Database properties: - type: Documentation url: https://docs.trychroma.com/cloud/sync/overview - type: OpenAPI url: openapi/chroma-cloud-api-openapi.yml - aid: chroma:python-client name: Chroma Python Client description: >- The Chroma Python Client is a first-party SDK for interacting with both self-hosted Chroma servers and Chroma Cloud. It provides a simple, developer-friendly interface with a core API of just four functions for managing collections, adding documents, and querying embeddings. The client handles automatic tokenization, embedding, and indexing of documents, making it straightforward to build AI applications that require vector similarity search. image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg humanURL: https://docs.trychroma.com/reference/python/client tags: - Embeddings - Python - SDK - Vector Database properties: - type: Documentation url: https://docs.trychroma.com/reference/python/client - type: SourceCode url: https://github.com/chroma-core/chroma - aid: chroma:javascript-client name: Chroma JavaScript Client description: >- The Chroma JavaScript and TypeScript Client is a first-party SDK for interacting with Chroma from JavaScript or TypeScript applications. The v3 rewrite focused on reducing bundle size and improving developer experience, making it well-suited for deployment on serverless platforms like Vercel. It supports both self-hosted Chroma instances and Chroma Cloud via the CloudClient class, providing collection management, document ingestion, and vector similarity search capabilities. image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg humanURL: https://docs.trychroma.com/reference/js/client tags: - Embeddings - JavaScript - SDK - TypeScript - Vector Database properties: - type: Documentation url: https://docs.trychroma.com/reference/js/client - type: SourceCode url: https://github.com/chroma-core/chroma-js common: - type: LinkedIn url: https://www.linkedin.com/company/trychroma - type: Website url: https://www.trychroma.com/ - type: Documentation url: https://docs.trychroma.com/docs/overview/introduction - type: Portal url: https://docs.trychroma.com/ - type: Login url: https://cloud.trychroma.com/ - type: Pricing url: https://docs.trychroma.com/cloud/pricing - type: Blog url: https://www.trychroma.com/blog - type: GitHubOrg url: https://github.com/chroma-core - type: SourceCode url: https://github.com/chroma-core/chroma - type: Discord url: https://discord.gg/MMeYNTmh3x - type: Twitter url: https://twitter.com/trychroma - type: License name: Apache License 2.0 url: https://github.com/chroma-core/chroma/blob/main/LICENSE - type: TermsOfService url: https://www.trychroma.com/tos - type: PrivacyPolicy url: https://www.trychroma.com/privacy - type: JSONLDContext url: json-ld/chroma-context.jsonld - type: JSONSchema url: json-schema/chroma-collection-schema.json - type: JSONSchema url: json-schema/chroma-record-schema.json - type: Spectral url: spectral/chroma-spectral.yml - name: Features type: Features data: - name: Document and Metadata Storage - name: Vector Similarity Search (Dense, Sparse, Hybrid) - name: Full-Text and Regex Search - name: Metadata Filtering - name: Multi-Modal Retrieval (Text, Image, Audio) - name: Automatic Tokenization and Embedding - name: Collection Management - name: Embedding Function Plugins - name: Self-Hosted and Cloud Deployments - name: Apache 2.0 Open Source License - name: EmbeddingProviders type: EmbeddingProviders data: - name: OpenAI - name: Cohere - name: Hugging Face - name: sentence-transformers - name: Google Vertex AI - name: Ollama - name: UseCases type: UseCases data: - name: RAG (Retrieval Augmented Generation) - name: Semantic Search - name: AI Agent Memory - name: Code Search (AST-Aware Chunking) - name: Recommendation Systems - name: Multi-Modal Search (Text + Images) - name: Question Answering Systems - name: Knowledge Base Querying - name: Standards type: Standards data: - name: OpenAPI Specification - name: REST/HTTP - name: Apache License 2.0 - type: LLMsTxt url: https://docs.trychroma.com/llms.txt maintainers: - FN: Kin Lane email: kin@apievangelist.com