ApiClo Docs

Good for autonomous coding tasks in VS Code. ApiClo can be connected in two ways.

Option A: OpenAI Compatible

1. 1

   Install Cline from the VS Code Marketplace and open Settings / API Configuration.

2. 2

   Select OpenAI Compatible as API Provider.

3. 3

   Set the full Base URL with /v1: https://apiclo.com/v1.

4. 4

   API Key: your sk-hub key. Model ID: claude-sonnet-5 or claude-opus-4-8.

5. 5

   Save the profile and first send the test: Reply only OK.

Option B: Anthropic Messages for native mode

1. 1

   If your Cline build requires the Anthropic provider, enable Use custom base URL.

2. 2

   Custom Base URL: https://apiclo.com . Do not add /v1 here; Cline calls /v1/messages itself.

3. 3

   API Key: your sk-hub key. Model: claude-sonnet-5 or claude-opus-4-8.

4. 4

   If the Anthropic native mode is unstable, return to Option A OpenAI-compatible.

After saving, send: Reply only OK. Second test: Look at the current folder and say whether README.md exists; do not change anything.

Roo Code uses almost the same setup as Cline, but the provider profile labels may differ.

1. 1

   Install Roo Code from VS Code Extensions and open the Roo Code panel.

2. 2

   Create an API key in ApiClo under API Keys.

3. 3

   Open API Configuration / Provider / Profile.

4. 4

   By default, choose an OpenAI-compatible profile: Base URL https://apiclo.com/v1 and an ApiClo model id.

5. 5

   Use Anthropic + custom base URL https://apiclo.com without /v1 only for native/advanced mode.

6. 6

   Save the profile, verify OK, then run a file task.

7. 7

   Second test: ask Roo to read the current folder and say whether README.md exists, without editing files.

For Kilo, use Custom Provider. Unlike Cline/Roo, the Base URL is usually entered with /v1.

1. 1

   Install Kilo Code from VS Code Extensions and open Settings / API Configuration.

2. 2

   Get an sk-hub API key in ApiClo -> API Keys.

3. 3

   Create a Custom Provider: Provider ID apiclaude, Display Name ApiClo.

4. 4

   For Claude models, choose Provider API: OpenAI Compatible and Base URL https://apiclo.com/v1 by default.

5. 5

   Use Provider API: Anthropic Messages only when Kilo explicitly needs native Messages mode.

6. 6

   Model ID: claude-sonnet-5, claude-opus-4-8, or claude-fable-5.

7. 7

   Save the provider and run two tests: Reply only OK; then read the project file list without edits.

Continue is configured through config.yaml. Give the model chat, edit, apply, and summarize roles.

1. 1

   Install Continue and open the configuration: Continue -> Settings -> Open config.yaml.

2. 2

   Save the old config.yaml before replacing it if you already have custom models.

3. 3

   Paste the block below and replace YOUR_API_KEY with your sk-hub key.

4. 4

   Restart Continue or run Reload Window in the IDE.

5. 5

   Test chat, edit, and apply on a small file before a heavy task.

name: ApiClo
version: 1.0.0
schema: v1
models:
  - name: Claude Sonnet 5
    provider: openai
    model: claude-sonnet-5
    apiBase: https://apiclo.com/v1
    apiKey: YOUR_API_KEY
    capabilities:
      - tool_use
    roles:
      - chat
      - edit
      - apply
      - summarize
    defaultCompletionOptions:
      temperature: 0
context:
  - provider: code
  - provider: docs
  - provider: diff
  - provider: terminal
  - provider: problems
  - provider: folder
  - provider: codebase

This example does not impose hard contextLength or maxTokens values. Continue uses the selected model's capabilities and shows the active configuration in Continue Console → Options.

In a long Agent session, click Compact conversation, the converging-arrows icon under the latest response. Once context reaches 60%, the same action is available from the context indicator beside the input. Continue keeps a technical summary and sends it with only the newer turns. This compacts history rather than truncating the active task. After compaction, inspect the next request in Continue Console: it should contain the summary and only newer turns, not hundreds of old tool_result blocks.

If Continue rejects provider: openai, use its OpenAI-compatible/custom provider with the same apiBase/apiKey/model. For model, use claude-sonnet-5 or claude-opus-4-8 without the apiclaude/ prefix.

For VS Code built-in Custom Endpoint, add models to the user configuration file.

1. 1

   Open the VS Code User settings folder and create chatLanguageModels.json if it does not exist.

2. 2

   Paste the JSON below and replace YOUR_API_KEY with your sk-hub key.

3. 3

   Check that url ends with /v1/chat/completions.

4. 4

   Run Developer: Reload Window.

5. 5

   In VS Code chat, choose Claude Sonnet 5 and send the test Reply only OK.

[
  {
    "name": "ApiClo",
    "vendor": "customendpoint",
    "apiKey": "YOUR_API_KEY",
    "apiType": "chat-completions",
    "models": [
      {
        "id": "claude-sonnet-5",
        "name": "Claude Sonnet 5",
        "url": "https://apiclo.com/v1/chat/completions",
        "toolCalling": true,
        "vision": true,
        "maxInputTokens": 1000000,
        "maxOutputTokens": 64000,
        "streaming": true
      },
      {
        "id": "claude-opus-4-8",
        "name": "Claude Opus 4.8",
        "url": "https://apiclo.com/v1/chat/completions",
        "toolCalling": true,
        "vision": true,
        "maxInputTokens": 1000000,
        "maxOutputTokens": 64000,
        "streaming": true
      }
    ]
  }
]

The simplest flow: connect ApiClo as an OpenAI-compatible endpoint.

1. 1

   Open Cursor Settings, Models, or API Keys.

2. 2

   Enable a custom OpenAI-compatible endpoint.

3. 3

   Base URL: https://apiclo.com/v1. API key: your sk-hub key.

4. 4

   Add model id: claude-sonnet-5 for regular work, claude-opus-4-8 for heavy reasoning/coding.

5. 5

   Save settings, choose the model in Cursor chat, and send Reply only OK.

6. 6

   If Cursor adds /v1 itself, leave the root URL without a second /v1.

Trae connects through Settings -> Models -> Add Model -> Custom Config.

1. 1

   Install Trae and sign in; otherwise the Models section may be hidden.

2. 2

   Open Settings -> Models -> Add Model -> Custom Config.

3. 3

   For Claude, choose API Format Anthropic Messages, URL https://apiclo.com or https://apiclo.com/v1 if Trae asks for the full /v1 endpoint.

4. 4

   For OpenAI Completions, use https://apiclo.com/v1 and model id claude-sonnet-5.

5. 5

   Paste the API Key, save the model, and run the Reply only OK test.

6. 6

   If Trae shows an empty answer, reduce max output and check the exact API Format.

Connect ApiClo as an OpenAI-compatible provider.

1. 1

   Open provider admin settings or the env configuration for your self-hosted UI.

2. 2

   Choose an OpenAI-compatible provider.

3. 3

   Set OPENAI_API_BASE_URL=https://apiclo.com/v1 and OPENAI_API_KEY=sk-hub-...

4. 4

   Add DEFAULT_MODEL=claude-sonnet-5 or choose the model in the UI.

5. 5

   Restart the UI container/process and send a short test.

If the UI adds /v1 itself, use root https://apiclo.com or remove the extra /v1 from the setting.

Claude Code usually expects an Anthropic-compatible base URL without /v1.

1. 1

   Check Node.js 18+: node --version.

2. 2

   Install Claude Code: npm install -g @anthropic-ai/claude-code@latest.

3. 3

   Check the install: claude --version.

4. 4

   For ApiClo, use ANTHROPIC_AUTH_TOKEN + ANTHROPIC_BASE_URL; ANTHROPIC_API_KEY is only for clients that require x-api-key.

5. 5

   Set CLAUDE_CODE_AUTO_COMPACT_WINDOW=180000 so Claude Code summarizes a long session before the 200k boundary. This does not limit response size.

6. 6

   First verify the gateway with a direct /v1/messages request, then start claude from the same shell session.

7. 7

   In Claude Code, run /status and confirm it shows the ApiClo base URL and active token source.

# macOS / Linux
export ANTHROPIC_AUTH_TOKEN="sk-hub-..."
export ANTHROPIC_BASE_URL="https://apiclo.com"
export ANTHROPIC_MODEL="claude-sonnet-5"
export CLAUDE_CODE_AUTO_COMPACT_WINDOW="180000"
claude

# Windows PowerShell
$env:ANTHROPIC_AUTH_TOKEN="sk-hub-..."
$env:ANTHROPIC_BASE_URL="https://apiclo.com"
$env:ANTHROPIC_MODEL="claude-sonnet-5"
$env:CLAUDE_CODE_AUTO_COMPACT_WINDOW="180000"
claude

{
  "env": {
    "ANTHROPIC_BASE_URL": "https://apiclo.com",
    "ANTHROPIC_AUTH_TOKEN": "sk-hub-...",
    "CLAUDE_CODE_AUTO_COMPACT_WINDOW": "180000"
  }
}

# macOS / Linux
curl -X POST "https://apiclo.com/v1/messages" \
  -H "Authorization: Bearer sk-hub-..." \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{"model":"claude-sonnet-5","max_tokens":1,"messages":[{"role":"user","content":"."}]}'

# Windows PowerShell
Invoke-RestMethod -Method Post -Uri "https://apiclo.com/v1/messages" `
  -Headers @{ "Authorization" = "Bearer sk-hub-..."; "anthropic-version" = "2023-06-01" } `
  -ContentType "application/json" `
  -Body '{"model":"claude-sonnet-5","max_tokens":1,"messages":[{"role":"user","content":"."}]}'

If the smoke returns JSON with msg_, the URL and key work. If it returns 401, the client sent the key with the wrong header; use ANTHROPIC_API_KEY only for an x-api-key scenario.

Codex can be pointed to ApiClo through a custom provider in config.toml.

1. 1

   In Codex Desktop / IDE, click the gear, then Codex Settings → Open config.toml; the CLI uses the same ~/.codex/config.toml.

2. 2

   Add the provider to the user-level config because project .codex/config.toml should not define provider/auth.

3. 3

   Set APICLAUDE_API_KEY to your sk-hub key. This variable name is chosen by env_key below.

4. 4

   Keep wire_api = responses: in current Codex this is the supported provider protocol.

5. 5

   Run codex in a test folder and verify Reply only OK.

model = "claude-sonnet-5"
model_provider = "apiclaude"

[model_providers.apiclaude]
name = "ApiClo"
base_url = "https://apiclo.com/v1"
env_key = "APICLAUDE_API_KEY"
wire_api = "responses"

# macOS / Linux
export APICLAUDE_API_KEY="sk-hub-..."
codex

# Windows PowerShell
$env:APICLAUDE_API_KEY="sk-hub-..."
codex

If Codex rejects the provider config, update Codex first. Do not switch wire_api to Chat Completions: current Codex docs describe responses as the supported provider protocol.

OpenCode supports provider config through opencode.json.

1. 1

   Go to a test project: cd ~/Desktop/my-project.

2. 2

   Install OpenCode: curl -fsSL https://opencode.ai/install | bash or npm install -g opencode-ai.

3. 3

   Check the install: opencode --version and opencode --help.

4. 4

   Create opencode.json in the project root and paste the config below.

5. 5

   Save the key with opencode providers login --provider apiclaude.

6. 6

   Run opencode and perform the OK/read-only test.

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "apiclaude": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "ApiClo",
      "options": {
        "baseURL": "https://apiclo.com/v1"
      },
      "models": {
        "claude-sonnet-5": {
          "name": "claude-sonnet-5"
        }
      }
    }
  },
  "model": "apiclaude/claude-sonnet-5"
}

OpenClaw can be connected through models.json with two provider modes.

1. 1

   Install OpenClaw for your platform and check openclaw --version.

2. 2

   Find the OpenClaw models file or create models.json in the config folder.

3. 3

   For Claude Messages mode, use provider apiclaude-messages with baseUrl https://apiclo.com.

4. 4

   For OpenAI Completions mode, use provider apiclaude-openai with baseUrl https://apiclo.com/v1.

5. 5

   Replace apiKey with your sk-hub key and run a read-only test in a project.

{
  "models": {
    "mode": "merge",
    "providers": {
      "apiclaude-messages": {
        "baseUrl": "https://apiclo.com",
        "apiKey": "sk-hub-...",
        "auth": "token",
        "api": "anthropic-messages",
        "models": [
          {
            "id": "claude-sonnet-5",
            "name": "claude-sonnet-5",
            "contextWindow": 1000000,
            "maxTokens": 64000
          }
        ]
      },
      "apiclaude-openai": {
        "baseUrl": "https://apiclo.com/v1",
        "apiKey": "sk-hub-...",
        "auth": "token",
        "api": "openai-completions",
        "models": [
          { "id": "claude-opus-4-8", "name": "claude-opus-4-8" }
        ]
      }
    }
  }
}

If Qwen Code is installed as an OpenAI-compatible client, OPENAI_* variables are enough.

1. 1

   Check Node.js: node --version.

2. 2

   Install Qwen Code: npm install -g @qwen-code/qwen-code@latest.

3. 3

   Check qwen --version and qwen --help.

4. 4

   For OpenAI-compatible mode, set OPENAI_API_KEY, OPENAI_BASE_URL, and OPENAI_MODEL.

5. 5

   If your Qwen Code build supports Anthropic env, you can use ANTHROPIC_AUTH_TOKEN + https://apiclo.com for Claude models.

6. 6

   Run qwen and perform the OK/read-only test.

export OPENAI_API_KEY="sk-hub-..."
export OPENAI_BASE_URL="https://apiclo.com/v1"
export OPENAI_MODEL="claude-sonnet-5"
qwen

$env:OPENAI_API_KEY="sk-hub-..."
$env:OPENAI_BASE_URL="https://apiclo.com/v1"
$env:OPENAI_MODEL="claude-sonnet-5"
qwen

Aider works through OpenAI-compatible variables.

1. 1

   Install Aider: python -m pip install -U aider-chat.

2. 2

   Open a terminal in a git project where test edits are safe.

3. 3

   Set OPENAI_API_BASE and OPENAI_API_KEY.

4. 4

   Run aider --model openai/claude-sonnet-5.

5. 5

   First ask it to explain a file; only allow edits after the connection is verified.

Pi connects through a model file and can use Anthropic Messages or OpenAI-compatible mode.

1. 1

   Install Pi in a macOS/Linux/WSL environment and check pi --version.

2. 2

   Create ~/.pi/agent and a models.json file.

3. 3

   For OpenAI-compatible mode, set baseUrl https://apiclo.com/v1 and model claude-sonnet-5.

4. 4

   For Anthropic Messages mode, use baseUrl https://apiclo.com and model claude-sonnet-5.

5. 5

   Pass the key through APICLAUDE_API_KEY or directly in local config, then run pi and perform the OK/read-only test.

{
  "providers": {
    "apiclaude-openai": {
      "baseUrl": "https://apiclo.com/v1",
      "apiKey": "${APICLAUDE_API_KEY}",
      "api": "openai-completions",
      "models": [
        { "id": "claude-sonnet-5", "name": "claude-sonnet-5" }
      ]
    }
  },
  "defaultModel": "apiclaude-openai/claude-sonnet-5"
}

Gemini CLI is not a good direct ApiClo target right now unless your build lets you set a custom OpenAI/Anthropic endpoint.

1. 1

   First check whether your Gemini CLI version has a custom base URL setting.

2. 2

   If custom endpoint is unavailable, do not try to override Google system variables: use Cline, Roo, Kilo, or Qwen Code.

3. 3

   If a custom OpenAI-compatible endpoint is available, use Base URL https://apiclo.com/v1, sk-hub API key, and model claude-sonnet-5.

4. 4

   After setup, run only a read-only test. If the client still calls the Google endpoint, switch to a supported CLI.

Built-in Hermes lives inside ApiClo: balance, model, memory, and history are managed from Agents.

1. 1

   Open Agents and choose Hermes.

2. 2

   Choose a model from the paid list: claude-sonnet-5, claude-opus-4-8, claude-sonnet-4-6.

3. 3

   For web pages, enable web context in chat; the URL will be read through the ApiClo reader/browser fallback.

4. 4

   To let Hermes work with your computer, download Desktop Bridge, create a pairing code, and grant only the needed file or folder permissions.

5. 5

   For long tasks, avoid switching models mid-chain without a reason; it helps cache and context.

The local router is useful when a client only talks to localhost or when you want to centralize the key on the machine.

1. 1

   Download ApiClo Desktop Bridge and run it on the same machine as the IDE/CLI.

2. 2

   Paste the upstream sk-hub key into Desktop Bridge.

3. 3

   Click Fetch models and make sure the model list loads.

4. 4

   Click Start router.

5. 5

   In the IDE/CLI, set Local Base URL http://127.0.0.1:18441/v1 and any non-empty client API key.

6. 6

   Test Reply only OK; if it does not answer, check that the local router is running and port 18441 is free.

Click Fetch models first, then Start router. In the IDE, use the local Base URL, not the public one.

Main route for IDEs, SDKs, and most self-hosted interfaces.

curl https://apiclo.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-5",
    "messages": [{"role": "user", "content": "Hi"}],
    "max_tokens": 512,
    "stream": true
  }'

Use this for clients expecting Claude Messages API.

curl https://apiclo.com/v1/messages \
  -H "x-api-key: YOUR_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-5",
    "max_tokens": 512,
    "messages": [{"role": "user", "content": "Hi"}]
  }'

Use this for clients that need the Responses wire API.

curl https://apiclo.com/v1/responses \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-5",
    "input": "Write a short checklist for release QA."
  }'

Good for scripts, backend jobs, and tests.

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://apiclo.com/v1",
)

response = client.chat.completions.create(
    model="claude-sonnet-5",
    messages=[{"role": "user", "content": "Hi"}],
    max_tokens=512,
)

print(response.choices[0].message.content)

Good for frontend-backed API routes and Node.js services.

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.APICLAUDE_API_KEY,
  baseURL: "https://apiclo.com/v1",
});

const response = await client.chat.completions.create({
  model: "claude-sonnet-5",
  messages: [{ role: "user", content: "Hi" }],
  max_tokens: 512,
});

console.log(response.choices[0].message.content);