Install Claude Code, create an AI Model Provider for Anthropic and an AI Model that targets it, then point Claude Code’s ANTHROPIC_BASE_URL at your local AI Gateway endpoint so all LLM requests pass through the gateway for monitoring and control.
This is a Konnect tutorial and requires a Konnect personal access token.
Create a new personal access token by opening the Konnect PAT page and selecting Generate Token.
Export your token to an environment variable:
export KONNECT_TOKEN='YOUR_KONNECT_PAT'Run the AI Gateway quickstart script to automatically provision a control plane and data plane in Kong Konnect, and configure your environment:
curl -Ls https://get.konghq.com/ai | bash -s -- -k $KONNECT_TOKEN This sets up a AI Gateway control plane named ai-quickstart, provisions a local data plane, and prints out the following environment variables export:
export AI_GATEWAY_ID=your-gateway-id
export KONNECT_TOKEN=$KONNECT_TOKEN
export KONNECT_CONTROL_PLANE_NAME=ai-quickstart
export KONNECT_CONTROL_PLANE_URL=https://us.api.konghq.com
export KONNECT_PROXY_URL='http://localhost:8000'Copy and paste these into your terminal to configure your session.
This tutorial uses kongctl to manage Konnect resources programmatically. We recommend keeping kongctl up to date with the latest version (1.13.0).
Verify the installation:
kongctl versionFor this task, you need an Anthropic API key.
Create a decK variable with your API key:
export ANTHROPIC_API_KEY='ANTHROPIC API KEY' curl -fsSL https://claude.ai/install.sh | bash claude --versionCreate an AI Model Provider entity to define your connection and store your authentication credentials:
kongctl apply -f - --auto-approve --pat "$KONNECT_TOKEN" << 'EOF'
ai_gateway_model_providers:
- ref: generic-anthropic
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: generic-anthropic
display_name: "generic-anthropic"
type: anthropic
config:
auth:
type: basic
headers:
- name: x-api-key
value: !secret {source: !env ANTHROPIC_API_KEY}
EOF
ai-quickstartreferences the AI Gateway created by the quickstart script in the prerequisites above, instead of creating a new one.
The AI Model Provider uses the following settings:
type: anthropic: Specifies that this provider connects to the Anthropic service using Anthropic’s standard API format.name: generic-anthropic: A unique identifier that AI Models will reference to route requests through this provider.config.auth.headers[0].value: !secret {source: !env ANTHROPIC_API_KEY}: Loads the API key from your environment at apply time so it is not embedded in the config, and kongctl redacts it in plan and diff output.Create an AI Model entity to declare which upstream models are available, configure how client requests are routed, and specify which AI Model Provider to use:
kongctl apply -f - --auto-approve --pat "$KONNECT_TOKEN" << 'EOF'
ai_gateway_models:
- ref: my-claude
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: my-claude
display_name: "my-claude"
type: model
formats:
- type: anthropic
config:
route:
paths:
- /
model:
body_param: model
values:
- my-claude
targets:
- name: claude-opus-4-8
provider: generic-anthropic
config:
type: anthropic
policies: []
capabilities:
- generate
EOFThe AI Model uses the following settings:
type: model: Specifies this is a synchronous model for request/response workloads.name: my-claude: A unique identifier for this model.formats: [type: anthropic]: Declares that this model accepts requests in Anthropic-compatible format.config.route.paths: [/]: Configures the custom base path where this model’s routes will be accessible. Setting this to a unique value avoids clashes when you have multiple AI Models.capabilities: [generate]: Enables the text generation capability. For a model using the anthropic format, the generate capability creates a /messages endpoint matching Anthropic’s native Messages API, so combined with your base path, clients send requests to /messages.targets: Specifies which upstream AI Model Provider model to route requests to. Here, provider: generic-anthropic references the AI Model Provider we created earlier, and name: claude-opus-4-8 specifies which Anthropic model to call upstream.Now, we can start a Claude Code session that points it to the local AI Gateway endpoint:
export ANTHROPIC_BASE_URL=http://localhost:8000/
CLAUDE_CODE_DISABLE_UNKNOWN_MODEL_WINDOW_ENFORCEMENT=1 \
claude --allowedTools "WebSearch,Read" --model "my-claude"And ask a question to confirm that requests reach AI Gateway.
Tell me about the Madrid Skylitzes manuscript.Claude Code might prompt you approve its web search for answering the question. When you select Yes, Claude will produce a full-length response to your request:
The Madrid Skylitzes is a remarkable 12th-century illuminated Byzantine
manuscript that represents one of the most important surviving examples
of medieval historical documentation. Here are the key details:
What it is
The Madrid Skylitzes is the only surviving illustrated manuscript of John
Skylitzes' "Synopsis of Histories" (Σύνοψις Ἱστοριῶν), which chronicles
Byzantine history from 811 to 1057 CE - covering the period from the death
of Emperor Nicephorus I to the deposition of Michael VI.
Artistic Significance
- 574 miniature paintings (with about 100 lost over time)
- Lavishly decorated with gold leaf, vibrant pigments, and intricate
detailing
- Depicts everything from imperial coronations and battles to daily life
in Byzantium
- The only surviving Byzantine illuminated chronicle written in Greek
Unique Collaboration
The manuscript is believed to be the work of 7 different artists from
various backgrounds:
- 4 Italian artists
- 1 English or French artist
- 2 Byzantine artists