Database

Chroma

Open-source AI-native vector database designed for storing, searching, and retrieving embeddings to power LLM applications and semantic search.

Chroma MCP, Integrations & Automations for Enterprise AI Agents

Connect your AI agents to Chroma MCP in minutes. No field mapping. No code required. Adopt AI's zero-shot API discovery means your agents understand Chroma's schema on first contact - and can act on it instantly.

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What Your AI Agents Can Do

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Create Collection on Chroma

Creates a collection with name, optional metadata JSON, embedding function config. Returns collection id.

Query Multi on Chroma

Runs multiple query_embeddings in one request (batch nearest neighbor). Pass query_embeddings as JSON array of vectors.

Create Database on Chroma

Creates database under tenant.

Query With Filter on Chroma

Query with mandatory where JSON metadata filter preset.

Create Auth Token on Chroma

Creates an auth token (admin).

Peek Collection on Chroma

Gets a small sample via CHROMA_GET_DOCUMENTS with limit 5.

Collection Add From Text on Chroma

Adds documents with auto-generated sequential ids when ids omitted (server-dependent); pass documents JSON array.

Query And Include Embeddings on Chroma

Query with include embeddings in response for debugging.

Count Collections on Chroma

Returns count of collections (uses list endpoint if dedicated count is unavailable).

Update Documents on Chroma

Updates existing ids with new embeddings/documents/metadata.

Version on Chroma

Returns server version/build metadata. Use to confirm compatibility with client expectations.

Upsert Documents on Chroma

Upserts vectors/documents by id.

Update Collection on Chroma

Updates collection name or metadata (PUT/PATCH per server).

Query Collection on Chroma

Vector similarity query with query_embeddings or query_texts JSON arrays, n_results, where, where_document, include. Returns distances and payloads.

Add Documents on Chroma

Adds ids, embeddings, documents, metadatas, uris to a collection. Pass parallel JSON arrays as strings.

List Auth Tokens on Chroma

Lists auth tokens when server auth is enabled.

List Collections on Chroma

Lists collections in the tenant/database scope. Returns ids and metadata. Use before querying; for counts use CHROMA_COUNT_COLLECTIONS.

Query Simple on Chroma

Simplified query: collection_id + query_texts JSON array + n_results. Use when you only have text and default embedding.

Create Tenant on Chroma

Creates tenant (Chroma Cloud / multi-tenant servers).

Reset on Chroma

POST /reset — **destroys all collections and data** on the server. Use only when explicitly wiping dev data; never on production without confirmation.

Get Collection on Chroma

Gets collection metadata by id or name depending on server. Use CHROMA_LIST_COLLECTIONS to resolve ids.

Count Documents on Chroma

Counts records in collection.

Delete Auth Token on Chroma

Deletes auth token by id.

Get Tenant on Chroma

Gets tenant by name.

Delete Collection on Chroma

Deletes a collection and all vectors.

Get Documents on Chroma

Fetches documents/embeddings/metadata by ids or where filter.

Heartbeat on Chroma

GET /heartbeat — verifies Chroma is reachable. Returns nanosecond heartbeat. Use before any workload.

Get Or Create Collection on Chroma

Creates collection with get_or_create true to avoid duplicates.

Get Database on Chroma

Gets database metadata.

Delete Documents on Chroma

Deletes by ids or where metadata filter JSON.

Connect Chroma MCP using Adopt AI in 3 Simple Steps

Run a single command in your terminal to install the Chroma MCP server locally, no complex setup, no cloud dependency.
A browser window opens automatically, where you can securely authenticate with your Chroma account with one click.
Restart your AI client, and your agents instantly have full access to collections, embeddings, documents, and every Chroma object, ready to read, write, and automate.

Use Cases for Chroma MCP

1. Semantic Search & Retrieval

AI agents store and query document embeddings in Chroma to power natural language search across knowledge bases, wikis, and internal documentation.

2. RAG Pipeline Automation

AI agents use Chroma as the vector store in retrieval-augmented generation workflows, automatically indexing new documents and serving relevant context to LLMs.

3. Content Recommendation Engine

AI agents query Chroma embeddings to surface similar articles, products, or resources based on user behavior and content similarity.

4. Duplicate & Similarity Detection

Automatically detect near-duplicate content, support tickets, or records by comparing embeddings in Chroma, reducing redundancy across systems.

5. AI Model Evaluation & Testing

AI agents store test embeddings in Chroma and run similarity benchmarks to evaluate model performance, track drift, and compare embedding quality over time.

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Frequently Asked Questions

Do I need my own developer credentials to use Chroma MCP with Adopt AI?

No, you can get started immediately using Adopt AI's built-in Chroma integration. For production use, we recommend configuring your own API credentials for greater control and security.

Can I connect Chroma with other apps through Adopt AI?

Yes! Adopt AI supports multi-app workflows, so your AI agents can seamlessly move data between Chroma and LLM platforms, knowledge bases, search tools, and more.

Is Adopt AI secure?

Absolutely. Adopt AI is SOC 2 Type 2 certified and ISO/IEC 27001 compliant, and adheres to EU GDPR, CCPA, and HIPAA standards. All data is encrypted in transit and at rest, ensuring the confidentiality, integrity, and availability of your data. Learn more here.

What happens if the Chroma API changes?

Adopt AI maintains and updates all integrations automatically, so your agents always work with the latest API versions, no manual maintenance required.

Do I need coding skills to set up the Chroma integration?

Not at all. Adopt AI's zero-shot API discovery means your agents understand Chroma's schema on first contact. Setup takes minutes with no code required.

How do I set up custom Chroma MCP in Adopt AI?

For a step-by-step guide on creating and configuring your own Chroma API credentials with Adopt AI, see here.