Best AI Coding Assistants with MCP Support

Contents

Figure 1: Best AI Coding Assistants with MCP Support — the tool you pick decides how much MCP power you hand it

A year ago, "supports MCP" was a bragging point on a feature list. Today it is table stakes, and the interesting question has changed: how well does each coding assistant handle MCP, and how safely?

The differences show up where you would expect. Some tools make adding a server a one-line command. Others hand you a marketplace. Some share a single config file across the terminal and the editor, and some do not. A few ask you to approve every server before it runs, which matters more than most people realize.

This guide compares the main assistants on their MCP support, explains what to check, and flags the safety issues. I researched it in October 2026, and numbered brackets like [1] point to the sources at the end. This market changes monthly, so verify details against each tool's current documentation.

What "MCP Support" Actually Means

Nearly every tool claims it. Check these specifics before you believe it:

Question	Why it decides your setup
Transports	Does it run local servers (stdio) and connect to remote ones (HTTP)? One Claude Code guide describes stdio for local subprocesses, HTTP for remote servers, and SSE, which it calls legacy and deprecated [1].
Remote authentication	Does it handle OAuth sign-in for remote servers?
Config scopes	Can you define servers per project, per user, or for a whole team?
Shared config	Do the terminal and the editor read the same settings?
Approval controls	Does the tool ask before it runs a server or a tool, and can you set rules?
Discovery	Is there a marketplace or a registry, or do you edit files by hand?
Enterprise controls	Can an admin allow or block servers?

One June 2026 comparison says broad MCP support is table stakes now, and singles out Cline's one-click MCP marketplace and Claude Code's deep MCP support as standouts [2]. That is one source's opinion, so test the tools yourself.

The Contenders at a Glance

Tool	Form factor	MCP standout	Watch out
Claude Code	Terminal CLI, VS Code, JetBrains (beta), desktop, web	Scoped config that a team can share	Terminal-first, steeper learning curve [5]
Cursor	Standalone editor	AI-first editor with multi-model choice	You leave stock VS Code
GitHub Copilot	Extension across many editors	MCP inside the editor you already use	Depth varies by editor and plan [5]
Codex CLI	Terminal plus IDE extension	One config.toml shared by both	Sandbox and approval settings need review [3]
Cline	VS Code sidebar, other editors, CLI	One-click MCP marketplace	You pay model costs; review installs [2]
Windsurf / Devin Desktop	Agentic IDE	Agent-driven flow	Renamed and changed ownership [2]
JetBrains Junie / AI Assistant	JetBrains plugins	Stays inside JetBrains	Narrower ecosystem
Gemini CLI	Terminal	Free and open source	Hosted CLI path retired [2]

Claude Code

Claude Code is Anthropic's coding agent. It runs as a terminal CLI, and one 2026 comparison says it also runs as a VS Code extension, a JetBrains plugin in beta, a desktop app, and on the web — all sharing one engine, one CLAUDE.md file, one MCP config, and one set of settings [2].

Here is how its MCP setup works, based on Anthropic's documentation [1]:

1. Add a server with one command: claude mcp add --transport http <name> <url> for remote servers, and claude mcp add --transport stdio <name> -- <command> [args] for local ones.
2. Three scopes: local (default, only you, only this project), project (a .mcp.json file at the repo root that everyone who clones the project gets), and user (only you, all projects) [1].
3. Clear precedence: when a name appears in several places, Claude Code uses local first, then project, then user, then plugin-provided servers, then claude.ai connectors [1].
4. Approval prompts: Claude Code asks each developer for approval before it uses servers from a .mcp.json it has not seen before [1].
5. Import from Claude Desktop: claude mcp add-from-claude-desktop imports servers on macOS and WSL [1].

Multiple third-party comparisons describe Claude Code's MCP integration as the most mature of the major tools [4][5]. As always with rankings, treat that as one input and test it on your workflow. Note too that Claude Code is an Anthropic product, which I flag again below.

• Best for: terminal-first developers and teams that want shareable, scoped MCP config.
• Watch out: the CLI rewards terminal comfort, and one comparison notes a steeper learning curve [5].

Cursor

Cursor is a VS Code fork with AI built into the editor [4]. One comparison says it added MCP support in late 2025 and keeps its config in .cursor/mcp.json [4]. A CLI comparison says the Cursor CLI shares settings and MCP configuration with the Cursor IDE [3].

• Best for: developers who want an AI-first editor with multi-model choice.
• Watch out: it is a standalone editor, so you switch away from stock VS Code.

GitHub Copilot

Copilot is the lowest-friction option across editors. Comparisons list support in VS Code, JetBrains, Visual Studio, Neovim and Xcode, plus the Copilot coding agent that can take assigned GitHub issues [5]. A June 2026 cheat sheet lists MCP and ACP support [2].

Pricing changed this year: one source says Copilot moves to usage-based AI Credits on June 1, 2026 [5]. Check GitHub's current plan details.

• Best for: teams already invested in GitHub, and developers who want AI in their existing editor.
• Watch out: MCP depth and organization policies can vary by editor and plan, so check GitHub's docs for your setup.

OpenAI Codex CLI

A July-era CLI comparison says Codex CLI registers MCP servers with codex mcp add, and that the official IDE extension — which works in VS Code, Cursor and Windsurf — shares the same config.toml [3]. Sharing one config between terminal and editor is a real convenience.

• Best for: terminal-first developers in the OpenAI ecosystem.
• Watch out: check its sandbox and approval settings, which that comparison describes as three sandbox modes combined with an approval policy [3].

Cline

Cline is an open-source (Apache 2.0) agent that runs as a VS Code sidebar, with growing support across JetBrains, Cursor, Windsurf, Zed and Neovim [5]. It also has a standalone CLI, which that source says shipped in version 2.0 in February 2026 [3]. Comparisons credit it with a one-click MCP marketplace [2].

• Best for: developers who want vendor independence, bring-your-own-key models and easy server discovery.
• Watch out: you pay model API costs, and a marketplace makes installing unvetted servers very easy, so review what you install.

Windsurf (Now Devin Desktop)

One June 2026 source says Windsurf became Devin Desktop [2]. An earlier comparison says Windsurf added MCP support in early 2026 and lists its config at ~/.codeium/windsurf/mcp_config.json, while noting its MCP ecosystem is smaller [4]. Because of the rename, verify where the config lives in the current release.

• Best for: developers who like an agent-driven IDE flow.
• Watch out: the product has changed names and ownership, so check its current status and docs.

JetBrains Junie and AI Assistant

The June 2026 cheat sheet lists JetBrains Junie and AI Assistant with MCP support, and positions them for developers who want to keep their JetBrains setup [2].

• Best for: JetBrains users who want AI inside their IDE.

Gemini CLI

Gemini CLI appears in several comparisons as a free, open-source terminal agent with MCP support [2][5]. The same cheat sheet notes that Google retired the individual hosted CLI path [2], so check Google's current docs before you plan around it.

Quick Picks

• Deepest, scoped MCP config with team sharing: Claude Code [1].
• AI-first editor with MCP and multi-model choice: Cursor [3][4].
• MCP inside your existing editors, tied to GitHub: GitHub Copilot [2][5].
• Terminal agent with shared CLI and IDE config: Codex CLI [3].
• Open source with a one-click MCP marketplace: Cline [2][5].
• Agentic IDE (renamed): Windsurf, now Devin Desktop [2][4].
• JetBrains-native AI: Junie and AI Assistant [2].

The market churns fast. The same cheat sheet notes that Roo Code shut down and that tools changed names and prices within months [2]. Re-check any recommendation, including this one, before you commit a team.

What a Project Config Looks Like

Project-level MCP config lets a whole team share the same servers through version control. A typical shared file for a stdio server looks like this. The exact schema differs by tool, so check your tool's docs:

{
  "mcpServers": {
    "sqlite": {
      "command": "python",
      "args": ["./tools/sqlite_mcp.py"],
      "env": {"SQLITE_DB_PATH": "./dev.db"}
    }
  }
}

For Claude Code, the same idea is one command — claude mcp add --scope project ... — which writes to .mcp.json at the repo root [1]. Commit the file for tools everyone needs, and keep personal credentials in local or user scope, never in the shared file.

Security: Project Config Can Run Code

Here is the point most comparisons skip. A project-level MCP file can launch programs on your machine. If you clone an untrusted repository and your tool starts its servers automatically, you have run someone else's commands.

1. Keep approval prompts on. Claude Code asks before it uses a .mcp.json it has not seen [1]. Check what your tool does by default, and do not turn approvals off for convenience.
2. Read the config before you approve. Look at every command, args and URL.
3. Prefer least privilege. Use read-only credentials and narrow scopes, as my guides on database servers and MCP security explain.
4. Be careful with marketplaces. One-click installs make it easy to add servers you have not reviewed.
5. Keep secrets out of shared files. Use environment variables and per-user scopes.
6. Remember prompt injection. Text that servers return — issues, web pages, database rows — can try to steer the agent. Do not give one agent private data, untrusted content and outbound access at once.
7. Use admin controls if your team needs allowlists. Check which tools offer them.

How to Choose

Walk through these questions:

1. Where do you work? Terminal, a VS Code-style editor, or JetBrains?
2. Do you need team-shared MCP config? Look for project scopes and version-controlled files.
3. Do you need remote servers with sign-in? Check HTTP and OAuth support.
4. How important is model choice? Multi-model tools offer flexibility, single-vendor tools offer tighter integration.
5. What are your security rules? Look for approval controls and admin policies.
6. What does it cost? Prices and plans shifted a lot in 2026, and sources disagree, so check current pricing pages.
7. How stable is the product? Check ownership, renames and recent releases.

Run a One-Day Bake-Off

Do not pick from a table. Test two or three tools with the same server:

1. Pick one real server, such as a read-only database server or an issue tracker.
2. Install it in each tool, and time the setup.
3. Run the same three tasks that need the server's tools.
4. Check approvals: what does each tool ask before it runs a tool call?
5. Check sharing: can a teammate get the same setup from the repo?
6. Check failure behaviour: break the config, and see how clear the error is.
7. Review the logs and permissions each tool exposes.

Common Pitfalls

1. Choosing on the "supports MCP" checkbox. Depth varies.
2. Auto-approving everything. One poisoned server then has free rein.
3. Committing secrets to a shared config. Use environment variables.
4. Installing marketplace servers without review.
5. Ignoring product churn. Tools rename, merge and shut down [2].
6. Using one config format everywhere. Each tool has its own file and schema.
7. Granting broad access to "make it work." Start narrow.

Wrapping Up

For MCP, nearly every serious coding assistant now clears the bar. The real differences lie in config scopes, sharing between terminal and editor, approval controls, and how quickly you can add and review a server.

Pick two tools, test them with the same read-only server, and keep approvals on. The assistant that makes the safe path the easy path is usually the one worth keeping.

If you want to build the server you will test them with, start with the Python MCP server walkthrough or the low-level SDK version, and wire it into Claude Desktop to see the client side.

Frequently Asked Questions

Which AI coding assistants support MCP in 2026?

Most of the serious ones do: Claude Code, Cursor, GitHub Copilot, OpenAI Codex CLI, Cline, Windsurf (now Devin Desktop), JetBrains Junie and AI Assistant, and Gemini CLI all appear with MCP support in 2026 comparisons. Broad support is table stakes now, so the useful question is not whether a tool supports MCP but how it handles scopes, sharing, approvals and discovery. That detail is where the tools actually differ.

What is the difference between MCP config scopes?

Scope decides who gets a server and where the setting lives. Local scope is the default and applies only to you in that project. Project scope writes a shared file such as .mcp.json at the repository root, so everyone who clones the project inherits the servers. User scope applies to you across all projects. When the same server name appears in several scopes, the precedence order decides which definition wins.

Can a cloned repository run commands on my machine through MCP config?

Yes, and this is the part most comparisons skip. A project-level MCP file contains a command and arguments, so if your tool starts servers from that file automatically, cloning an untrusted repository and opening it can execute someone else's commands. Keep approval prompts on, read every command, argument and URL before approving, and do not disable approvals for convenience. Prefer tools that ask before using a .mcp.json they have not seen.

Why does the same MCP server behave differently in two assistants?

Because transports, scopes, approval behaviour and tool-result policies differ between clients. One tool may support only local stdio servers, another may handle remote HTTP with OAuth, and a third may share one config between its terminal and editor surfaces. A server that works in one client can fail in another for reasons that have nothing to do with the server code. Test the pair, not the server in isolation.

Should I use a marketplace to install MCP servers?

Marketplaces make discovery easy and review harder. A one-click install removes the step where you read the command, the arguments and the permissions, which is exactly the step that protects you. If you use one, treat every installed server as untrusted code: read the definition, check what credentials it receives, and start with read-only access rather than broad scopes.

How should a team choose an MCP-capable assistant?

Do not choose from a comparison table. Pick one real read-only server, such as a database reader or an issue tracker, install it in two or three candidate tools, and time the setup. Then run the same three tasks that need that server's tools, check what each tool asks before running a call, confirm whether a teammate can reproduce the setup from the repository, and break the config deliberately to see how clear the error is.

Sources

• [1] Anthropic, Claude Code MCP documentation — claude mcp add, local, project and user scopes, .mcp.json, scope precedence, approval prompts, add-from-claude-desktop, and the three transports with SSE marked legacy and deprecated: code.claude.com/docs/pt/mcp-quickstart (Portuguese-language version), plus Scrimba's Claude Code MCP guide for the scope table and precedence order, and a DEV Community team-setup guide for approvals and desktop import. A second DEV configuration guide on scopes, transports and precedence returned 404 when checked and is cited by description only.
• [2] David Veksler, "AI coding agents compared" — cheat sheet updated June 2026 covering renames, shutdowns, MCP and ACP notes, table stakes, the Cline marketplace, Windsurf becoming Devin Desktop, Copilot credits, Gemini CLI, Junie and AI Assistant: cheatsheets.davidveksler.com
• [3] Toolsbase, "AI Coding CLI Comparison 2026" — Codex CLI codex mcp add and shared config.toml, Cursor CLI sharing config with the IDE, Cline CLI 2.0 shipping February 2026, and the sandbox-plus-approval model: toolsbase.dev
• [4] Shyft, "Cursor vs Windsurf vs Claude Code" — MCP config file locations, support timelines, Cursor as a VS Code fork, and Windsurf's smaller MCP ecosystem: shyft.ai
• [5] Scrimba, "Best AI Coding Assistants 2026" — Copilot's editor coverage and coding agent, Cline as Apache 2.0 with wide editor support, the Claude Code learning curve, and the June 1, 2026 AI Credits change: scrimba.com, plus the Skills Hub "Compare" roundup on MCP adoption, which was unreachable when checked and is cited by description only.

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