AI Agent for Chroma MCP
Integrate Chroma MCP—the open-source embedding database—seamlessly with your AI workflows. Enable your LLM apps to store, search, and manage memory with blazing speed. Automate document ingestion, semantic search, collection management, and metadata filtering to empower knowledge-rich, context-aware AI solutions.
Effortless Vector Database Integration
Quickly connect your LLM applications to Chroma MCP to power advanced memory and context retrieval. Manage ephemeral, persistent, cloud, or self-hosted clients for ultimate flexibility and scale. Add, query, and organize data collections with optimized vector search and full text search capabilities.
- Flexible Storage Modes.
- Choose between in-memory, file-based, cloud, or self-hosted clients for tailored scalability and performance.
- Collection Management.
- Create, modify, and delete collections with support for pagination, metadata, and advanced configuration.
- Optimized Vector Search.
- Leverage HNSW and full text search for instant, accurate retrieval of relevant information.
- Embedding Function Selection.
- Integrate with industry-leading embedding models like Cohere, OpenAI, Jina, VoyageAI, and Roboflow.
Automated Document Operations
Streamline adding, querying, updating, and deleting documents. Use advanced metadata filters, semantic search, and customizable IDs for powerful document workflows and scalable knowledge bases.
- Bulk Document Ingestion.
- Add documents in bulk with optional metadata and custom IDs for streamlined onboarding.
- Semantic and Metadata Query.
- Execute semantic searches and filter results by metadata or content for precise retrieval.
- Granular Document Control.
- Update or delete documents by ID or filter, ensuring your knowledge base stays organized.
Cloud & API Integration
Securely connect to Chroma Cloud or your own self-hosted Chroma instance via API keys, environment variables, and custom configuration. Automate secure access and enable robust, remote data workflows for distributed AI teams.
- Chroma Cloud Support.
- Connect instantly to Chroma Cloud for managed scalability and security.
- Secure API Access.
- Leverage environment variables and API keys for safe, automated integrations.
- Self-Hosted Flexibility.
- Deploy on your own infrastructure for full control over your data and compliance.
MCP INTEGRATION
Available Chroma MCP Integration Tools
The following tools are available as part of the Chroma MCP integration:
- chroma_list_collections
List all collections with pagination support to help manage and discover collection resources.
- chroma_create_collection
Create a new collection with optional HNSW configuration and embedding function selection.
- chroma_peek_collection
View a sample of documents within a collection to quickly inspect stored content.
- chroma_get_collection_info
Get detailed information about a specific collection, including configuration and statistics.
- chroma_get_collection_count
Retrieve the number of documents contained within a collection.
- chroma_modify_collection
Update a collection's name or metadata for organizational and descriptive purposes.
- chroma_delete_collection
Delete a collection to remove all associated documents and metadata.
- chroma_add_documents
Add documents to a collection with optional metadata and custom IDs for flexible storage.
- chroma_query_documents
Query documents using semantic search, advanced filtering, and metadata criteria.
- chroma_get_documents
Retrieve documents by IDs or filters with pagination support for efficient data access.
- chroma_update_documents
Update existing documents' content, metadata, or embeddings within a collection.
- chroma_delete_documents
Delete specific documents from a collection using IDs or filter criteria.
Get Started with Chroma MCP Server
Experience the fastest way to build LLM apps with memory. Book a personalized demo or try FlowHunt free to see how Chroma integrates seamlessly with your AI workflows.
What is Chroma
Chroma is an open-source search and retrieval database designed specifically for AI applications. It offers powerful vector, full-text, regex, and metadata search capabilities, making it ideal for handling complex data queries in AI-driven environments. Chroma allows users to develop locally and seamlessly scale to petabyte levels in the cloud, leveraging object storage for efficient data management. The platform is serverless, ensuring fast, cost-effective, and reliable search and retrieval operations. Chroma is widely used for embedding, storing, and searching large-scale AI-generated data, enabling developers and organizations to build and deploy advanced AI solutions with ease.
Capabilities
What we can do with Chroma
With Chroma, users can implement robust search and retrieval functionalities for AI applications. The platform supports efficient handling of vector data and metadata, making it ideal for managing, querying, and scaling AI workloads.
- Vector Search
- Perform fast similarity searches on high-dimensional vector embeddings.
- Full-Text Search
- Retrieve documents using traditional text-based search queries.
- Metadata Filtering
- Filter and organize results based on metadata attributes.
- Serverless Scaling
- Develop locally and scale seamlessly to the cloud with serverless infrastructure.
- Integration Ready
- Integrate Chroma with popular AI and machine learning frameworks for end-to-end workflows.
How AI Agents Benefit from Chroma
AI agents can leverage Chroma to efficiently store, retrieve, and manage large volumes of embedding and metadata-rich data. This enables agents to rapidly access relevant information, personalize responses, and scale their operations as data grows. Chroma’s serverless architecture and integration capabilities further streamline AI workflows, making it an essential backbone for intelligent, data-driven applications.