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Databases · Integration guide

How to connect Chroma to any AI IDE (Claude/Codex/Cursor/VS Code/Antigravity)

Before you start, install GateRook and connect it to your AI development environment: Claude Desktop, Codex, Cursor, Antigravity or VS Code.

Connect your AI app

Collections and records of Chroma and Chroma Cloud: metadata-filtered pages and nearest-neighbour search by embedding or record. Upserts and deletes wait for approval.

The screenshots show GateRook 2.0.0: the Chroma form, the endpoint selector, and this connector’s actual tool preview. The form and preview have not been saved. Select a screenshot to open it at full size.

1. Create a connection and enter the settings

In GateRook, open Connections, select Add connection, search for Chroma, choose its card and select Continue to configure.

Use a Chroma server or Chroma Cloud endpoint. A local persistent database folder is not a server URL.

Identify the tenant and database that contain your collections. A self-managed default setup commonly uses default_tenant and default_database; Chroma Cloud supplies its own values.

Enter a Name, for example chroma-demo. Your AI app uses this name to choose the connection.

Enter Server URL, Tenant and Database, then narrow Collections to the required collection names or patterns.

Under Authentication, choose the header scheme the server expects: Token in X-Chroma-Token (Chroma Cloud), Bearer token in Authorization, or No authentication for a server that intentionally checks none. Supply API key or token when required.

For a private CA, enter CA certificate (PEM) under Advanced.

Choose Development, Staging or Production to match the service. Review the connector’s limit and access settings before continuing.

GateRook 2.0.0 Configure Chroma form before saving.
The Chroma configuration form. Enter your own connection settings before testing.

2. Test the connection and add it to an endpoint

Select Continue to test. GateRook checks the settings from your computer. Review the result and resolve any connection, certificate or permission error before continuing.

If collections are missing, verify the tenant and database as well as the credentials. A query vector must have the dimensions used by the collection; inspect the collection before asking for similarity results.

After the test passes, select Continue to add to an endpoint. Choose the endpoint your AI app uses, review its tool modes, then select Save connection. GateRook offers default as the starter endpoint.

GateRook endpoint selector with default selected; no connector tool list is shown.
Choose the endpoint your AI app uses. This selector is shared across connector types; the next screenshot shows this connector’s own tools.

3. Use the connection from your AI IDE

After saving Chroma on the endpoint and passing its connection test, ask your AI app to use chroma-demo, or the name you chose. If its tools are missing, confirm the endpoint assignment and refresh the MCP connection or start a new chat.

The preview below shows this connector’s default tools before saving. The table explains what each tool can do; connection settings, credentials and endpoint policies can restrict access further.

Chroma connector tool names and default modes in the GateRook 2.0.0 endpoint preview.
Chroma tools in the Development endpoint preview. This is an unsaved preview, not a successful service call.

Start with a small read request. Replace example resource names with existing resources your connection may access. Open Activity after the call to inspect its connection, tool, arguments, policy decision and result metadata.

Ask your AI, for example

  • “List the collections available through chroma-demo.”
  • “Describe the support_docs collection on chroma-demo.”
  • “Using chroma-demo, fetch the document with ID faq-123 from support_docs.”
Tools your AI gets
ToolWhat it doesStarts as
vector_list_collectionsList the permitted Chroma collections in the configured tenant and database.Read only
vector_describe_collectionShow a collection’s ID, tenant, database, available dimension and metric, collection metadata, embedding function name and record count.Read only
vector_getFetch records by text ID or read a bounded metadata-filter page, including stored documents. Include embeddings only when requested.Read only
vector_queryFind nearest records using an embedding vector or a stored record ID, with a metadata filter and topK limit. Text query input is not supported by this connector.Read only
vector_upsertWrites up to 100 records to one collection; a record with an existing id replaces it. You approve the exact records. Never retried.Approval
vector_deleteDeletes records by id, up to 1,000 of one collection. You approve the exact ids; nothing else is deleted. Never retried.Approval

You can change each tool’s mode on the endpoint. Every call your AI makes appears in Activity.

Service documentation

Keep exploring

Chroma Cloud

Connect Chroma Cloud to Claude, Codex, Cursor, VS Code or Antigravity with GateRook. Follow setup, connection testing and tool access with screenshots.

PostgreSQL

Connect PostgreSQL to Claude, Codex, Cursor, VS Code or Antigravity in three steps. Your AI runs read queries; changes wait for your approval.

MySQL

Connect MySQL to Claude, Codex, Cursor, VS Code or Antigravity in three steps. GateRook keeps the password; your AI reads data and asks before changes.

Browse all integration guides

Your local MCP gateway and firewall.

Connect Chroma to your AI IDE.

Choose a connector. Start with read-only access. Approve changes and inspect the audit trail.

Read the getting started guide

Get GateRook

Download GateRook 2.0.0 for your Mac, or get the Windows app from Microsoft Store.

macOS

Version 2.0.0 for Apple Silicon (arm64). This download does not support Intel Macs.

Open the DMG and drag GateRook to Applications.

Windows

Available for free from Microsoft Store. Install GateRook and receive updates through the Store.

macOS release notes and checksums (opens in a new tab)