Claude Code vs Cursor vs GitHub Copilot: Picking One for a Team

For a team, Claude Code, Cursor and GitHub Copilot are closer than their marketing suggests: all three plan, edit files, run commands, use MCP tools, read an AGENTS.md, and can run work in the cloud. What separates them is where the team’s control sits. Copilot’s sits in GitHub, in organization and enterprise policies, so it suits teams whose code, reviews and permissions already live there. Cursor’s sits in its team dashboard, so it suits teams that want everyone in one editor with the settings pushed from one place. Claude Code’s sits in managed settings that reach every surface it runs on, the terminal, editors, desktop and web, so it suits teams that want one agent in laptops, scripts and CI alike. Pick the one whose control point matches how your team already works, and expect some people to use more than one.

This page covers team concerns only. How each agent handles a task day to day is in the head-to-head posts: Claude Code vs Cursor, Claude Code vs GitHub Copilot and GitHub Copilot agent vs Cursor agent.

The three side by side

• Where it runs. Claude Code: terminal, VS Code and JetBrains, desktop app, web. Cursor: its own editor, a command-line agent and cloud agents. Copilot: VS Code and other editors, Copilot CLI, and the cloud agent on GitHub.
• Shared instructions. Claude Code: CLAUDE.md, or AGENTS.md when there is no CLAUDE.md. Cursor: .cursor/rules, AGENTS.md, and a root CLAUDE.md. Copilot: .github/copilot-instructions.md, *.instructions.md and AGENTS.md.
• Shared MCP servers. Claude Code: .mcp.json in the repository. Cursor: .cursor/mcp.json. Copilot: .vscode/mcp.json or a root .mcp.json in VS Code, and repository settings for the cloud agent.
• Central policy. Claude Code: managed settings from the admin console, device management or a file. Cursor: the team dashboard, with most controls on Enterprise. Copilot: organization and enterprise policies in GitHub.
• Seeing usage. Claude Code: an analytics dashboard on Team and Enterprise, OpenTelemetry on any provider. Cursor: team analytics, and audit logs and OpenTelemetry export on Enterprise. Copilot: usage metrics dashboards for organizations and enterprises.
• Work in the cloud. Claude Code: cloud sessions, a GitHub Action and Code Review. Cursor: cloud agents and Bugbot. Copilot: the cloud agent and Copilot code review.
• Where the code must be hosted. Claude Code and Cursor work on any local repository; Cursor’s cloud agents clone from GitHub, GitLab, Bitbucket or Azure DevOps. Copilot’s cloud agent works only on GitHub.

One setup the whole team shares

The cheapest team win is the same in all three: commit the setup. Put shared rules in one AGENTS.md, since all three read it, add a two-line CLAUDE.md that imports it if anyone uses Claude Code, and commit each tool’s MCP file so a new starter gets the same servers on day one. The file-by-file map is in AI context files compared. What a repository file cannot do is stop someone from ignoring it, which is where central policy comes in.

What an admin can enforce

Claude Code: Anthropic’s organization setup guide↗ (opens in a new tab) describes managed settings delivered from the Claude admin console on Team and Enterprise plans, through macOS or Windows device policy, or as a file on each machine, and they take precedence over user and project settings. Permission allow and deny lists merge, so developers can add to the managed lists but not remove from them. Admins can turn off the mode that skips permissions, require the sandbox, ship an organization-wide CLAUDE.md, restrict which models appear, and allow or deny MCP servers.

Cursor: the team dashboard holds privacy settings, single sign-on and usage settings. Cursor’s page on model and integration management↗ (opens in a new tab) lists the Enterprise controls: which models members may use, a block on personal API keys, and an MCP allowlist that lets only approved servers run. Allowlisting a server does not install it for people; a team marketplace distributes approved servers.

Copilot: policies are set per organization or enterprise in GitHub. For MCP, GitHub’s MCP overview↗ (opens in a new tab) says the MCP servers in Copilot policy is disabled by default and governs only members with Copilot Business or Enterprise seats from that organization; admins can also point Copilot at an MCP registry and allow only servers from it in supported editors and Copilot CLI. For the cloud agent, repository owners can opt repositories out, and MCP servers are set per repository.

The common gap: each policy governs its own tool. If half the team uses Cursor and half uses Copilot, you maintain two MCP allowlists, and nothing in either one knows about the other.

What you can see afterward

• Claude Code: the analytics dashboard shows adoption and contribution on Team and Enterprise, OpenTelemetry export works on every provider, and a gateway in front of the model gives request-level logs with the person’s identity.
• Cursor: according to its compliance and monitoring page↗ (opens in a new tab), Enterprise audit logs record sign-ins, membership, roles, API keys, settings and integrations, but never prompts, agent output or generated code. Token and tool-call telemetry is a separate OpenTelemetry export.
• Copilot: GitHub’s usage metrics dashboard↗ (opens in a new tab) is available to organization and enterprise owners and people with a metrics role, with charts for agent adoption. Cloud agent commits are signed and link to the session log.

All three answer “how much is the team using it”. None of them answers “which piece of planned work did that session finish, and who checked it”. That is a record of the work, not the tool, and it is covered in an audit trail for AI agents.

Where your code goes

• Claude Code: Anthropic says it does not train models on code or prompts from Team, Enterprise, API or cloud provider plans, and offers zero data retention to qualified Enterprise accounts. Teams can also run it through Amazon Bedrock, Google Cloud or Microsoft Foundry, though cloud sessions, routines and Code Review need a claude.ai account.
• Cursor: its privacy and data governance page↗ (opens in a new tab) says code is never used for training with Privacy Mode on, that Privacy Mode is on by default for Enterprise teams and can be enforced for a team, and that cloud agents are the only feature that stores code, as encrypted copies deleted when the agent finishes.
• Copilot: code already on GitHub stays there for the cloud agent, which works in a GitHub Actions environment with restricted internet access. Read GitHub’s own terms for your Copilot plan alongside the other two.

Work that runs without a laptop

Each has a way to hand off a task and meet it again as a pull request, and each reviews pull requests. The detail is in Cursor cloud agents, the GitHub Copilot coding agent and Claude Code in GitHub Actions; how to fit agent review into your process is in AI agents for PR review. For a team, the question is which system your reviewers already open every morning. If that is GitHub, Copilot’s cloud agent and review need the least new habit.

You may not have to pick just one

The three overlap more each quarter. VS Code can run a session on a Claude harness beside Copilot’s own. The Claude Code extension installs in Cursor, and Cursor reads a root CLAUDE.md. So a team can standardize on one editor and let people choose the agent inside it. The cost is governance: every tool someone uses is one more policy to keep in step.

A checklist for choosing

1. Where is the code hosted? If it is not all on GitHub, Copilot’s cloud agent cannot reach the rest.
2. Where do people work? A terminal-and-scripts team leans to Claude Code; an editor-first team to Cursor or Copilot.
3. Which controls do you need, and on which plan? Several of Cursor’s controls are Enterprise only; Copilot’s MCP policy covers Business and Enterprise seats; Claude Code’s console delivery needs Team or Enterprise.
4. Who reads the logs? Decide whether you need adoption numbers, admin audit events or per-request logs, and check which plan gives them.
5. What must never happen? Write it as a deny rule or an allowlist in the tool, not as a sentence in a prompt.
6. Where will the list of work live? Not in any of the three; see below.

One list of work, whichever tool picks it up

Each tool keeps its own record: a transcript, a chat, a cloud session under one person’s account. Put the work on a board all three reach over MCP. On fenbs, each connects to https://fenbs.ai/api/mcp with a browser sign-in, or, for the Copilot cloud agent, a token issued under Settings with a name, scopes and an optional expiry. Each assistant then acts on your behalf within your role, and History records which one changed what. Tasks move through To Do, Next Up, In Progress and Completed, each with a note of the problem, a plan and a test status, and the rules on the Decisions and rules page are read by every connected assistant first. fenbs has no sprints, due dates or assignee field; it is the shared list, not a planning suite.

# Claude Code, shared through .mcp.json
claude mcp add --transport http --scope project fenbs https://fenbs.ai/api/mcp

// Cursor: .cursor/mcp.json
{ "mcpServers": { "fenbs": { "url": "https://fenbs.ai/api/mcp" } } }

// Copilot in VS Code: .vscode/mcp.json
{ "servers": { "fenbs": { "type": "http", "url": "https://fenbs.ai/api/mcp" } } }