GitHub Copilot

Start with 1: run Copilot on AI Reserve models, so every Copilot chat is metered on your AI Reserve key. 2 is optional on top: the AI Reserve assistant for account questions inside Copilot Chat.

	What developers see	How it is paid for
1. Run Copilot on AI Reserve models (start here)	our models in Copilot’s own model picker, for Chat, agent mode and edits, made the default	an AI Reserve key, billed like any API call; no Copilot premium requests
2. The AI Reserve assistant (optional)	account tools inside the Copilot they already use: budget, usage, prices, API keys, or a second opinion from a named model	sign in with the portal account; only the questions handed to our models are billed

Any AI Reserve key works, and it is what pays. Paste a key you already have from the portal’s API Keys page or create one there. Whatever that key belongs to, you, your team or your organization, is what gets debited, with its spend caps and model rules applied. GitHub bills nothing extra, and GitHub states that requests to a provider you bring do not count against Copilot premium-request allowances. Inline ghost-text completions are the one thing that stays on GitHub’s own models.

1. Run Copilot on AI Reserve models

Three ways to get our models into the picker. They differ only in who sets them up.

Way	Who	Where it shows up	Needs
AI Reserve extension	each developer, one minute	VS Code	an AI Reserve account (one browser sign-in; the key is created for you)
Organization-wide custom models	the GitHub admin, once	every client, including Copilot Chat on github.com	GitHub Enterprise with Copilot Business or Enterprise seats
Custom Endpoint or Copilot CLI	each developer	VS Code, Copilot CLI	a key; the manual version of the extension

For yourself: the AI Reserve extension

The extension registers AI Reserve as a model provider in VS Code. Install it, open Copilot’s model picker → Manage Models → AI Reserve, sign in once in your browser, and every model you can use appears in the picker with its price and context window. The sign-in creates a personal API key for you and keeps it in VS Code’s secret storage, so there is nothing to copy and no portal visit; because the key is yours, your usage shows under your name and your team in the portal. Blocked models never show; budget refusals come back as one plain sentence.

Install

Until the Marketplace listing is live, download the .vsix (0.1.3) and in VS Code open the Extensions view → the ··· menu at its top right → Install from VSIX…. The portal page switches to a one-click install the day the listing is live.

Copilot model picker → Manage Models → AI Reserve, or run AI Reserve: Sign in from the Command Palette, and click Sign in. Your browser opens on AI Reserve; sign in with your work account and approve the one Manage permission the extension asks for. A key named GitHub Copilot · VS Code is created under your name (visible and revocable on the API Keys page) and saved in VS Code; the sign-in token itself is used for that one step and discarded. Remote windows (SSH, Codespaces) work the same way. Already have a key? Choose Paste a key instead, or run AI Reserve: Paste an API key.

Pick a model

Auto lets AI Reserve route each request; or pick any model by name. New catalog models appear on their own with their real name, price and context window (the list refreshes when the picker opens, in the background every 30 minutes, or right away with AI Reserve: Refresh the model list). Settings: aireserve.models shows only the ids you list, aireserve.includeConsentGatedModels also lists providers that need a one-time consent in the portal, aireserve.refreshIntervalMinutes changes the background cadence (0 turns it off).

Make it the default (optional)

Say yes when the extension offers it after sign-in, or run AI Reserve: Make AI Reserve the default for new chats. It sets VS Code’s own "chat.defaultModel": "aireserve", so every new Copilot chat starts on AI Reserve Auto instead of GitHub’s model; you can still switch within a conversation. Our entries are easy to spot in the picker: they sit under the AI Reserve heading and every detail line starts with “AI Reserve”.

Making AI Reserve the default for everyone (recommended). Two levers, both your GitHub or IT admin’s: (1) VS Code’s ChatDefaultModel enterprise policy (VS Code 1.127+, pushed by MDM or group policy like any VS Code policy) forces chat.defaultModel to aireserve on every managed machine, and users cannot override it; (2) on GitHub Enterprise, AI controls → Copilot → Configure models lets you disable GitHub’s hosted chat models and turn off the default availability policy so new GitHub models do not reappear, leaving only the AI Reserve custom models in the picker. Together they guarantee every chat, agent and edit request is metered on your AI Reserve key, while inline ghost-text completions keep working as before: they stay on GitHub’s models either way. No admin yet? Each developer can pin AI Reserve models to the top of the picker (hover a model → pin) and hide GitHub’s under Manage Models (hover → eye icon).

For your whole organization: custom models

On GitHub Enterprise with Copilot Business or Enterprise seats, a GitHub admin adds AI Reserve once as an OpenAI-compatible custom model provider (a GitHub public preview). Our models then appear at the bottom of every developer’s picker, under the enterprise name, in VS Code, JetBrains, the Copilot CLI and Copilot Chat on github.com, with nothing to install per developer and one organization key paying for everything.

Spend per department. GitHub sends every developer’s traffic on the key its admin pasted, so one organization key cannot tell departments apart. For department budgets, mint one key per department instead (Connect GitHub Copilot → One department, a team-scoped key that spends from that team’s budget) and add each as its own entry in GitHub, named AI Reserve · <department>; GitHub prefixes every model with the entry name, so developers pick their own. Per-developer attribution needs no GitHub admin step at all: each developer signs in once through the extension, which creates a key under their name, and their usage lands on them and their team.

Get the key

An AI Reserve administrator mints it on the Connect GitHub Copilot page, for the whole organization or for one department (it appears on the organization’s API Keys page and can be revoked there at any time).

Turn on the policy

Enterprise owner: AI controls → Copilot → Policies → Enable custom models. Without it, organization admins do not see the Custom models tab.

Add the key

Enterprise: AI controls → Copilot → Configure custom models → Add API key. Organization: Settings → Code, planning, and automation → Copilot → Models → Custom models → Add API key. Provider OpenAI-compatible, name AI Reserve, base URL https://api.aireserve.com/v1, the organization key, and the model ids to expose (case-sensitive): claude-sonnet-4-6, claude-opus-4-8, gpt-5.5, gpt-5.4-mini, gemini-2.5-pro, plus auto to let AI Reserve pick per request. Any chat model id from the catalog works.

Enable and verify

Enable the models for your organizations and save. Within a few minutes a developer sees them in the picker; the first request appears on the organization’s Analytics page. When AI Reserve adds a model, we email the GitHub admins set up in the portal the new ids to add to this list (one line, same screen); auto and the extension pick new models up on their own.

Without the extension: Custom Endpoint and Copilot CLI

Have the aireserve CLI? The installer’s agent picker offers GitHub Copilot CLI whenever the copilot command is on the machine (aireserve configure copilot-cli names it outright), and writes the Copilot CLI variables below as a managed block in your shell profile; open a new terminal and run copilot. aireserve unconfigure copilot-cli takes the block out again. One further command writes both lists below from the live catalog and keeps them current: every tool-calling chat model, AI Reserve · Auto first, each with its own context window, merged into VS Code’s Custom Endpoint file for every VS Code channel installed on the machine (other providers in that file are left alone), plus the Copilot CLI variables as a managed block in your shell profile. It reuses the key aireserve configure stored, so nothing is pasted: the VS Code file keeps the ${input:aireserveApiKey} prompt, and the shell block reads the key out of the CLI’s credential store when a shell starts, never into the file.

aireserve copilot sync            # VS Code Custom Endpoint file + Copilot CLI variables
aireserve copilot sync --dry-run  # preview every change as a diff, write nothing
aireserve copilot status          # what is managed, how many models, last sync

The session-start sync the CLI installs for Claude Code and Codex refreshes both on its 12-hour cadence, so new models appear without another command. No CLI on this machine, or prefer to do it by hand? The manual steps:

VS Code Custom Endpoint, by hand

VS Code’s built-in Custom Endpoint provider does what the extension does, by hand (Microsoft’s guide):

Open the Command Palette and run Chat: Manage Language Models (the gear icon in the chat model picker opens the same editor).
Select Add Models → Custom Endpoint. Name the group AI Reserve, enter a display name and your aireserve_api_… key when asked, and pick Chat Completions as the API type.
VS Code opens chatLanguageModels.json. Replace the generated entry with:

chatLanguageModels.json

[
  {
    "name": "AI Reserve",
    "vendor": "customendpoint",
    "apiKey": "${input:aireserveApiKey}",
    "apiType": "chat-completions",
    "models": [
      {
        "id": "auto",
        "name": "AI Reserve · Auto",
        "url": "https://api.aireserve.com/v1/chat/completions",
        "toolCalling": true,
        "vision": true,
        "maxInputTokens": 128000,
        "maxOutputTokens": 16000
      }
    ]
  }
]

Save, then choose AI Reserve · Auto from the model picker. To pin a model instead, add an entry to models with any id from the catalog, same url, one object per model, and set maxInputTokens / maxOutputTokens to that model’s published window (for example claude-sonnet-4-6 is 1,000,000 / 128,000; the figures are on each model’s catalog page, and the portal page prints a ready-made snippet with them filled in). Keep toolCalling: true (agent mode needs it); set vision only on models that accept images (per-model table).

The key never lands in the file. ${input:aireserveApiKey} is an input variable: VS Code prompts for the value once and keeps it in secret storage, so chatLanguageModels.json is safe to sync or commit. On Copilot Business or Enterprise this is governed by the Bring Your Own Language Model Key in VS Code policy, on by default; if Add Models is missing, an administrator has turned it off.

Copilot CLI variables, by hand

The Copilot CLI takes the same key through its bring-your-own-provider variables (GitHub’s guide):

export COPILOT_PROVIDER_BASE_URL="https://api.aireserve.com/v1"
export COPILOT_PROVIDER_TYPE="openai"
export COPILOT_PROVIDER_API_KEY="<your aireserve_api_… key>"
export COPILOT_MODEL="auto"

2. Add the AI Reserve assistant to Copilot Chat

Optional, on top of section 1. To chat with our models, pick them in the model picker (section 1); the assistant is for your account: budget, usage, prices and keys, plus a second opinion from a named model. With an AI Reserve model selected in the picker, the assistant runs entirely on AI Reserve as well; with a GitHub model selected, GitHub’s model orchestrates the call and a Copilot premium request is spent alongside ours. GitHub retired App-based Copilot Extensions on 10 November 2025; the AI Reserve MCP server is how tools and an assistant reach Copilot Chat today. The server publishes OAuth discovery with dynamic client registration, so every IDE signs you in from a browser tab with your portal account, and each person sees only what they can already see in the portal. It works alongside whichever model Copilot is running on, ours or GitHub’s.

Copilot Business or Enterprise: a GitHub admin must turn on the MCP servers in Copilot policy once (it is off by default) under the organization’s or enterprise’s Copilot policies. If your company restricts MCP to an approved registry, add AI Reserve’s registry entry. Copilot Pro and Free need nothing.

VS Code
JetBrains, Visual Studio, Eclipse, Xcode
Copilot CLI and the Copilot app
github.com: cloud agent and code review

Add to VS Code

Opens VS Code and asks to install aireserve.

Add to VS Code Insiders

Same, for the Insiders build.

Click Install, then Allow when VS Code asks to sign in to AI Reserve. A browser tab signs you in with your portal account and the tools appear in agent mode. Nothing happened? Paste this into .vscode/mcp.json in your workspace (or your user profile’s mcp.json):

.vscode/mcp.json

{
  "servers": {
    "aireserve": {
      "type": "http",
      "url": "https://api.aireserve.com/mcp"
    }
  }
}

VS Code 1.99 or newer. Verify with MCP: List Servers in the Command Palette.

Open Copilot Chat in Agent mode, click the tools icon (Configure your MCP server) → Add MCP Tools, paste the same servers JSON, and click Allow on the sign-in prompt:

mcp.json

{
  "servers": {
    "aireserve": {
      "type": "http",
      "url": "https://api.aireserve.com/mcp"
    }
  }
}

One command; the first use opens the AI Reserve sign-in in your browser (Copilot CLI 1.0.11 or newer). The GitHub Copilot desktop app picks up the CLI’s servers automatically, or add it in the app under Customize → MCP → Add custom server (type HTTP, URL https://api.aireserve.com/mcp, no headers):

    copilot mcp add --transport http aireserve https://api.aireserve.com/mcp

Or declare it in ~/.copilot/mcp-config.json (the same mcpServers shape works in a repository-root .mcp.json, shared with everyone who clones the repo):

~/.copilot/mcp-config.json

{
  "mcpServers": {
    "aireserve": {
      "type": "http",
      "url": "https://api.aireserve.com/mcp",
      "tools": [
        "*"
      ]
    }
  }
}

The agent that works on issues and pull requests (and Copilot code review) runs without a browser, so it uses a management token instead of signing in:

Mint a token on API Keys → Management Keys in the portal.
In the repository, add it as an Agents secret named COPILOT_MCP_AIRESERVE_TOKEN (Settings → Environments → copilot). GitHub only exposes COPILOT_MCP_* names to MCP servers.
Paste this under Settings → Copilot → MCP servers and save:

MCP configuration

{
  "mcpServers": {
    "aireserve": {
      "type": "http",
      "url": "https://api.aireserve.com/mcp",
      "headers": {
        "Authorization": "Bearer $COPILOT_MCP_AIRESERVE_TOKEN"
      },
      "tools": [
        "whoami",
        "list-models",
        "get-model",
        "get-connection-guide",
        "send-message"
      ]
    }
  }
}

Tools are listed explicitly because the cloud agent calls them without asking first; send-message spends from the token owner’s budget. Copilot Chat on github.com itself only talks to GitHub’s own MCP server (a GitHub limit, the same for every vendor): to use AI Reserve models in that chat, put them in the model picker.

Try it

In Copilot Chat, switch to Agent mode and type:

using fable 5.1 ping me

Copilot looks the model up with list-models, sends your message with send-message, and replies with the answer and the exact model that produced it (Model: claude-fable-5-1). The same loop is one command, /mcp.aireserve.ask-model, and #send-message pins the tool when you want to be explicit. Other things to ask once connected: “which models can I use and what do they cost”, “what did my team spend this week”, “how much budget do I have left”, “list my API keys”. Every answer is scoped to what your portal role can already see; anything that spends money or changes your account asks for confirmation first. The full surface is in the MCP tool reference.

For GitHub admins: assistant rollout checklist

MCP servers in Copilot → Enabled. Organization: Settings → Copilot → Policies. Enterprise: AI controls → Copilot → Policies (or “No policy” to let each organization decide).
Restricting MCP to a registry? Add the AI Reserve entry to it: the server is https://api.aireserve.com/mcp, streamable HTTP, OAuth sign-in, nothing to run on developer machines.
Share the install. Send developers this page, or commit the ready-made .vscode/mcp.json and repository-root .mcp.json to shared repositories so every clone has the assistant. Repository admins who want the cloud agent on it paste this configuration.
Verify with a pilot group: using fable 5.1 ping me answers with a Model: line, and the request appears on the developer’s Analytics page.
Set spend caps on the AI Reserve side (organization, per-team and per-member budgets) from the portal’s Members page.

What about Copilot on github.com?

Copilot Chat on github.com gets our models through the organization-wide custom models setup; that is the only way any vendor reaches its picker. The assistant cannot be added there: GitHub wires only its own MCP server into that chat.
The Copilot cloud agent and Copilot code review also run on github.com and take the assistant through the repository configuration in the github.com tab above.

Verify

Pick an AI Reserve model in Copilot Chat and send any message; it streams and the request appears on your Analytics page seconds later, metered against the key it came in on. Administrators also see each request as a row in the portal’s Event Log (Observe → Event Log): the model, the key it came in on, who made it, cost and latency, with requests from the extension labelled GitHub Copilot under Spend by tool. For the assistant, using fable 5.1 ping me in agent mode answers with a Model: line.

Getting started

Connect your tool

GPU Infrastructure

AWS Hub

Capabilities

Migrate

Performance

Data & privacy

Reliability

1. Run Copilot on AI Reserve models

For yourself: the AI Reserve extension

For your whole organization: custom models

Without the extension: Custom Endpoint and Copilot CLI

2. Add the AI Reserve assistant to Copilot Chat

Add to VS Code

Add to VS Code Insiders

Try it

For GitHub admins: assistant rollout checklist

What about Copilot on github.com?

Verify

​1. Run Copilot on AI Reserve models

​For yourself: the AI Reserve extension

​For your whole organization: custom models

​Without the extension: Custom Endpoint and Copilot CLI

​2. Add the AI Reserve assistant to Copilot Chat

Add to VS Code

Add to VS Code Insiders

​Try it

​For GitHub admins: assistant rollout checklist

​What about Copilot on github.com?

​Verify

1. Run Copilot on AI Reserve models

For yourself: the AI Reserve extension

For your whole organization: custom models

Without the extension: Custom Endpoint and Copilot CLI

2. Add the AI Reserve assistant to Copilot Chat

Try it

For GitHub admins: assistant rollout checklist

What about Copilot on github.com?

Verify