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Arize Ai Provider Integration

  • 1.9k installs
  • 40 repo stars
  • Updated July 27, 2026
  • arize-ai/arize-skills

How to register, list, update, and delete LLM provider credentials stored in Arize.

About

The Arize AI Integration skill creates, reads, updates, and deletes credential stores for any LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom endpoints) within an Arize account or space. Developers use it to register provider API keys or IAM roles once, then reference the integration ID in evaluators and other Arize workflows. Key workflows include listing integrations to find existing credentials, creating new integrations with provider-specific flags (API key, base URL, provider metadata), rotating keys via update, and managing scoping rules to control which spaces can access each integration.

  • Support for 8+ LLM providers with provider-specific auth (API keys, IAM roles, GCP service accounts, bearer tokens)
  • Partial update semantics - change only the fields you need without re-entering full config
  • Scoping rules to restrict integration visibility to specific spaces within an Arize account
  • List and filter integrations by name, with pagination for large result sets
  • Integration IDs returned as base64 identifiers for use in downstream evaluator and experiment commands

Arize Ai Provider Integration by the numbers

  • 1,875 all-time installs (skills.sh)
  • +166 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #250 of 4,386 Backend & APIs skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

arize-ai-provider-integration capabilities & compatibility

Capabilities
create ai integrations for any llm provider · list and filter integrations by name and space · update integration credentials and config · delete integrations with confirmation · apply scoping rules to restrict access
Works with
openai · anthropic · aws · gcp
Use cases
api development · token optimization
Platforms
macOS · Windows · Linux · WSL
Runs
Hosted SaaS
Pricing
Free
From the docs

What arize-ai-provider-integration says it does

Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM)
arize-ai-provider-integration.md § name/description
npx skills add https://github.com/arize-ai/arize-skills --skill arize-ai-provider-integration

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Listed on Skillselion
Installs1.9k
repo stars40
Security audit3 / 3 scanners passed
Last updatedJuly 27, 2026
Repositoryarize-ai/arize-skills

What it does

Store and manage LLM provider credentials in Arize for evaluators and platform features.

Who is it for?

Teams using Arize evaluators or LLM-as-judge workflows that need to manage credentials for multiple providers.

Skip if: Local LLM deployments not exposed via provider APIs; direct credential passing in code.

When should I use this skill?

User mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

What you get

Credentials are stored once and referenced by integration ID across evaluators, experiments, and platform workflows.

  • corrected ax profile configuration

By the numbers

  • 8+ supported LLM providers: OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom
  • 3 authentication types: default, proxy_with_headers, bearer_token
  • List pagination supports 1-100 results per page

Files

SKILL.mdMarkdownGitHub ↗

Arize AI Integration Skill

`SPACE` — Most --space flags and the ARIZE_SPACE env var accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list.
Note: ai-integrations create does not accept --space — AI integrations are account-scoped. Use --space only with list, get, update, and delete.

Concepts

  • AI Integration = stored LLM provider credentials registered in Arize; used by evaluators to call a judge model and by other Arize features that need to invoke an LLM on your behalf
  • Provider = the LLM service backing the integration (e.g., openAI, anthropic, awsBedrock)
  • Integration ID = a base64-encoded global identifier for an integration (e.g., TGxtSW50ZWdyYXRpb246MTI6YUJjRA==); required for evaluator creation and other downstream operations
  • Scoping = visibility rules controlling which spaces or users can use an integration
  • Auth type = how Arize authenticates with the provider: default (provider API key), proxy_with_headers (proxy via custom headers), or bearer_token (bearer token auth)

Prerequisites

Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.

If an ax command fails, troubleshoot based on the error:

  • command not found or version error → see references/ax-setup.md
  • 401 Unauthorized / missing API key → run ax profiles show to inspect the current profile. If the profile is missing or the API key is wrong, follow references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keys
  • Space unknown → run ax spaces list to pick by name, or ask the user
  • LLM provider call fails (missing OPENAI_API_KEY / ANTHROPIC_API_KEY) → run ax ai-integrations list --space SPACE to check for platform-managed credentials. If none exist, ask the user to provide the key or create an integration via the arize-ai-provider-integration skill
  • Security: Never read .env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. If credentials are not available through these channels, ask the user.

---

List AI Integrations

List all integrations accessible in a space:

ax ai-integrations list --space SPACE

Filter by name (case-insensitive substring match):

ax ai-integrations list --space SPACE --name "openai"

Paginate large result sets:

# Get first page
ax ai-integrations list --space SPACE --limit 20 -o json

# Get next page using cursor from previous response
ax ai-integrations list --space SPACE --limit 20 --cursor CURSOR_TOKEN -o json

Key flags:

FlagDescription
--spaceSpace name or ID to filter integrations
--nameCase-insensitive substring filter on integration name
--limitMax results (1–100, default 15)
--cursorPagination token from a previous response
-o, --outputOutput format: table (default) or json

Response fields:

FieldDescription
idBase64 integration ID — copy this for downstream commands
nameHuman-readable name
providerLLM provider enum (see Supported Providers below)
has_api_keytrue if credentials are stored
model_namesAllowed model list, or null if all models are enabled
enable_default_modelsWhether default models for this provider are allowed
function_calling_enabledWhether tool/function calling is enabled
auth_typeAuthentication method: default, proxy_with_headers, or bearer_token

---

Get a Specific Integration

ax ai-integrations get NAME_OR_ID
ax ai-integrations get NAME_OR_ID -o json
ax ai-integrations get NAME_OR_ID --space SPACE   # required when using name instead of ID

Use this to inspect an integration's full configuration or to confirm its ID after creation.

---

Create an AI Integration

Before creating, always list integrations first — the user may already have a suitable one:

ax ai-integrations list --space SPACE

If no suitable integration exists, create one. The required flags depend on the provider.

OpenAI

ax ai-integrations create \
  --name "My OpenAI Integration" \
  --provider openAI \
  --api-key $OPENAI_API_KEY

Anthropic

ax ai-integrations create \
  --name "My Anthropic Integration" \
  --provider anthropic \
  --api-key $ANTHROPIC_API_KEY

Azure OpenAI

ax ai-integrations create \
  --name "My Azure OpenAI Integration" \
  --provider azureOpenAI \
  --api-key $AZURE_OPENAI_API_KEY \
  --base-url "https://my-resource.openai.azure.com/"

AWS Bedrock

AWS Bedrock uses IAM role-based auth. Provide the ARN of the role Arize should assume via --provider-metadata:

ax ai-integrations create \
  --name "My Bedrock Integration" \
  --provider awsBedrock \
  --provider-metadata '{"role_arn": "arn:aws:iam::123456789012:role/ArizeBedrockRole"}'

Vertex AI

Vertex AI uses GCP service account credentials. Provide the GCP project and region via --provider-metadata:

ax ai-integrations create \
  --name "My Vertex AI Integration" \
  --provider vertexAI \
  --provider-metadata '{"project_id": "my-gcp-project", "location": "us-central1"}'

Gemini

ax ai-integrations create \
  --name "My Gemini Integration" \
  --provider gemini \
  --api-key $GEMINI_API_KEY

NVIDIA NIM

ax ai-integrations create \
  --name "My NVIDIA NIM Integration" \
  --provider nvidiaNim \
  --api-key $NVIDIA_API_KEY \
  --base-url "https://integrate.api.nvidia.com/v1"

Custom (OpenAI-compatible endpoint)

ax ai-integrations create \
  --name "My Custom Integration" \
  --provider custom \
  --base-url "https://my-llm-proxy.example.com/v1" \
  --api-key $CUSTOM_LLM_API_KEY

Supported Providers

ProviderRequired extra flags
openAI--api-key <key>
anthropic--api-key <key>
azureOpenAI--api-key <key>, --base-url <azure-endpoint>
awsBedrock--provider-metadata '{"role_arn": "<arn>"}'
vertexAI--provider-metadata '{"project_id": "<gcp-project>", "location": "<region>"}'
gemini--api-key <key>
nvidiaNim--api-key <key>, --base-url <nim-endpoint>
custom--base-url <endpoint>

Optional flags for any provider

FlagDescription
--model-nameAllowed model name (repeat for multiple, e.g. --model-name gpt-4o --model-name gpt-4o-mini); omit to allow all models
--enable-default-modelsEnable the provider's default model list
--function-calling-enabledEnable tool/function calling support
--auth-typeAuthentication type: default, proxy_with_headers, or bearer_token
--headersCustom headers as JSON object or file path (for proxy auth)
--provider-metadataProvider-specific metadata as JSON object or file path

After creation

Capture the returned integration ID (e.g., TGxtSW50ZWdyYXRpb246MTI6YUJjRA==) — it is needed for evaluator creation and other downstream commands. If you missed it, retrieve it:

ax ai-integrations list --space SPACE -o json
# or by name/ID directly:
ax ai-integrations get NAME_OR_ID

---

Update an AI Integration

update is a partial update — only the flags you provide are changed. Omitted fields stay as-is.

# Rename
ax ai-integrations update NAME_OR_ID --name "New Name"

# Rotate the API key
ax ai-integrations update NAME_OR_ID --api-key $OPENAI_API_KEY

# Change the model list (replaces all existing model names)
ax ai-integrations update NAME_OR_ID --model-name gpt-4o --model-name gpt-4o-mini

# Update base URL (for Azure, custom, or NIM)
ax ai-integrations update NAME_OR_ID --base-url "https://new-endpoint.example.com/v1"

# Restrict visibility to specific spaces (full replace — lists all spaces that should have access)
ax ai-integrations update NAME_OR_ID \
  --scopings '[{"space_id": "SPACE_GLOBAL_ID", "scoping_type": "include"}]'

Add --space SPACE when using a name instead of ID. Any flag accepted by create can be passed to update.

`--scopings` flag: Controls which spaces can use this integration. Accepts a JSON array of scoping rules. Replaces all existing scopings on update. Use ax spaces list -o json to find space global IDs.

---

Delete an AI Integration

Warning: Deletion is permanent. Evaluators that reference this integration will no longer be able to run.

ax ai-integrations delete NAME_OR_ID --force
ax ai-integrations delete NAME_OR_ID --space SPACE --force   # required when using name instead of ID

Omit --force to get a confirmation prompt instead of deleting immediately.

---

Troubleshooting

ProblemSolution
ax: command not foundSee references/ax-setup.md
401 UnauthorizedAPI key may not have access to this space. Verify key and space ID at https://app.arize.com/admin > API Keys
No profile foundRun ax profiles show --expand; set ARIZE_API_KEY env var or write ~/.arize/config.toml
Integration not foundVerify with ax ai-integrations list --space SPACE
has_api_key: false after createCredentials were not saved — re-run update with the correct --api-key or --provider-metadata
Evaluator runs fail with LLM errorsCheck integration credentials with ax ai-integrations get INT_ID; rotate the API key if needed
provider mismatchCannot change provider after creation — delete and recreate with the correct provider

---

Related Skills

  • arize-evaluator: Create LLM-as-judge evaluators that use an AI integration → use arize-evaluator
  • arize-experiment: Run experiments that use evaluators backed by an AI integration → use arize-experiment

---

Save Credentials for Future Use

See references/ax-profiles.md § Save Credentials for Future Use.

Related skills

Forks & variants (1)

Arize Ai Provider Integration has 1 known copy in the catalog totaling 1k installs. They canonicalize to this original listing.

FAQ

Are AI integrations account-scoped or space-scoped?

Account-scoped at creation; use --space with list, get, update, delete to control visibility. Scoping rules restrict which spaces can use each integration.

What auth types does Arize support?

default (provider API key), proxy_with_headers (custom headers), bearer_token (bearer token auth).

Can I change a provider after creating an integration?

No. Delete and recreate with the correct provider.

Is Arize Ai Provider Integration safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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