Clients

The gateway publishes ready-to-paste configuration for the tools people actually use. Nothing on these endpoints is secret — your key is always a placeholder you fill in locally — so they are public and CORS-open.

VS Code (Copilot Chat, Custom Endpoint)

VS Code's Custom Endpoint language-model provider takes a JSON object describing the models to add to the picker. The gateway serves it prebuilt:

GET https://ai.codai.ro/vscode/chatLanguageModels.json

curl.exe -s https://ai.codai.ro/vscode/chatLanguageModels.json | Set-Clipboard

The picker gets three entries, each a fixed model identity:

The served config sets headers that keep the gateway a transparent transport: X-Codai-Disable-Subagents: 1, X-Codai-No-Recall: 1, X-Codai-Compact: off, plus X-Codai-Thinking: 1 with a per-alias budget and X-Codai-Cache: 1. Copilot owns orchestration and the transcript; the gateway never runs a second agent loop behind it.

Two companion endpoints publish a curated settings baseline: GET /vscode/settings.json (VS Code user settings) and GET /vscode/.copilot/settings.json (Copilot CLI ~/.copilot/settings.json).

GitHub Copilot CLI (BYOK)

Copilot CLI runs in bring-your-own-key mode when COPILOT_PROVIDER_BASE_URL is set — GitHub sign-in is not required. codai is a drop-in provider.

$env:COPILOT_PROVIDER_API_KEY = 'codai_xxxxxxxx'
Invoke-RestMethod https://ai.codai.ro/copilot/env.ps1 | Out-File env.ps1
. .\env.ps1   # dot-source: sets the vars and launches copilot

GET /copilot/config returns the same values as JSON, including the alternative aliases you may use as the wire model (codai-fast, codai-deep, codai-agent, codai-max, codai-explorer, codai-vision) and the capability flags (streaming, tool calling, vision and prompt caching are on; GitHub-hosted memory and remote delegation stay GitHub-routed and are unavailable in BYOK mode).

Persistent memory for BYOK sessions

BYOK mode loses GitHub's memory. Add the codai MCP server instead:

mkdir -p ~/.codai
curl -fsSL -o ~/.codai/mcp-codai-memory.mjs https://ai.codai.ro/copilot/mcp-bridge.mjs
curl -s https://ai.codai.ro/copilot/mcp.json   # paste `mcpServers` into ~/.copilot/mcp-config.json

The snippet registers a local stdio bridge, not an http server: the CLI does not expand ${ENV} placeholders in http headers, so a remote server with a templated Authorization header sends the literal placeholder and hangs the 60 s handshake. The bridge reads CODAI_API_KEY or COPILOT_PROVIDER_API_KEY from the environment and forwards JSON-RPC to /mcp. Replace ~ in args with your absolute home directory — the CLI does not expand it.

Cursor, Continue, Cline, Zed and other OpenAI-compatible tools

Any client with an OpenAI-compatible provider option works. Set:

If the tool lets you set custom headers, X-Codai-Effort: high or max is the one worth adding. If it offers a model list, it can read GET /v1/models with your key.

Claude Code and Anthropic-native tools

Set the Anthropic base URL to the root and the key to your codai key:

export ANTHROPIC_BASE_URL='https://ai.codai.ro'
export ANTHROPIC_API_KEY='codai_xxxxxxxx'
export ANTHROPIC_MODEL='codai'

POST /v1/messages accepts both Authorization: Bearer and x-api-key, so the SDK's default header works unchanged.

MCP server

The gateway is itself a remote MCP server (Streamable HTTP, spec 2025-11-25, wire-compatible with 2025-06-18):

POST https://ai.codai.ro/mcp

Tools: chat, list_models, memory_search, memory_store, memory_list, memory_forget, memory_graph. It also exposes prompts (slash commands), resources (codai://models, codai://memory/recent) and prompt-argument completion.

Two ways to authenticate:

• API key — Authorization: Bearer codai_…. Use this from scripts or via the stdio bridge above.
• OAuth 2.1 — clients that support it (VS Code, Claude Desktop, Claude Code, ChatGPT connectors) need no key at all. Point them at the URL; an unauthenticated request returns 401 with a WWW-Authenticate: Bearer resource_metadata=… challenge, and GET /.well-known/oauth-protected-resource/mcp points to auth.codai.ro for self-onboarding.

{
  "servers": {
    "codai": { "type": "http", "url": "https://ai.codai.ro/mcp" }
  }
}

Send Accept: text/event-stream and a chat tool call streams notifications/progress while in flight, then the JSON-RPC result. Every MCP request passes the same rate limiter as /v1, and tool calls that reach an upstream write a usage record.

Which one should I use?

• You live in VS Code → the Custom Endpoint config. Effort dial, three roles, keychain-stored key.
• You live in a terminal → Copilot CLI BYOK plus the memory bridge.
• You use another editor → its OpenAI-compatible provider with the /v1 base URL.
• You are wiring an agent framework → the SDKs, or the OpenAI/Anthropic SDK against the matching base URL.