Sfmc MCP Server

mcp-server-sfmc

MCP server providing Salesforce Marketing Cloud language intelligence — AMPscript, SSJS, and GTL — as Model Context Protocol tools, resources, and prompts for AI-assisted development and code review. It also ships a searchable index of mirrored Salesforce Help for Marketing Cloud Engagement administration and setup (business units, Journey Builder, Automation Studio, tenants, and similar topics), with explicit scoping vs Marketing Cloud Next (a separate product).

Built on sfmc-language-lsp, the same engine that powers the SFMC Language Service VS Code extension.

VS Code MCP Server Gallery (@mcp)

This package is registered with the official MCP Registry as io.github.JoernBerkefeld/mcp-server-sfmc so it can appear in Visual Studio Code when you use the @mcp filter in the Extensions view (see the publish quickstart). Enable chat.mcp.gallery.enabled if the gallery does not show.

The registry only stores metadata; the server still runs locally via stdio (for example npx -y mcp-server-sfmc@latest). This is separate from @contribute:mcp, which lists VS Code extensions that contribute MCP definitions — use the SFMC Language Service for that path.

After publishing metadata (see Publish an MCP Server or the release workflow), you can confirm the entry with:

curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.JoernBerkefeld/mcp-server-sfmc"

VS Code without manual MCP config

If you use the SFMC Language Service extension (1.101+), it registers this MCP server for discovery in VS Code — you normally do not need to edit .vscode/mcp.json or run npm install for that path; VS Code still launches the published package via npx when the server starts.

For other editors, or if you prefer explicit configuration, use the npx or install options below.

Using this package without the VS Code extension

You do not have to install the VS Code extension. Pick one way to run the server:

None of these replace the VS Code extension for editing (syntax, LSP, snippets); they only expose the MCP server to tools that speak the Model Context Protocol.

CI templates and sfmc-review-diff

Ready-to-copy workflows (GitHub Actions, GitLab CI, Jenkins, Azure Pipelines, Bitbucket Pipelines) live under ci-templates/. They run eslint-plugin-sfmc on changed files and sfmc-review-diff on the PR/MR unified diff. See ci-templates/README.md for what each file does and how the two checks differ.

What it gives your AI assistant

Connecting AI clients

VS Code (1.99+) + GitHub Copilot — manual mcp.json

If you are not using the SFMC Language Service extension’s built-in MCP registration, add a .vscode/mcp.json file to your project (or copy it from this repo):

{
  "servers": {
    "sfmc": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"]
    }
  }
}

Open the file in VS Code — a Start button appears at the top. Click it to launch the server. Open GitHub Copilot Chat in Agent mode and the SFMC tools appear automatically.

Cursor

Add to your Cursor settings (~/.cursor/mcp.json or project-level .cursor/mcp.json):

{
  "mcpServers": {
    "sfmc": {
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"]
    }
  }
}

Restart Cursor. The tools are available in Agent mode.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "sfmc": {
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"]
    }
  }
}

Restart Claude Desktop.

Windsurf

Add to your Windsurf MCP settings (~/.codeium/windsurf/mcp_config.json):

{
  "mcpServers": {
    "sfmc": {
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"]
    }
  }
}

Local install (faster startup than npx)

npm install -g mcp-server-sfmc

Then replace "command": "npx", "args": ["-y", "mcp-server-sfmc@latest"] with:

"command": "mcp-server-sfmc",
"args": []

Tools

Resources

Prompts

Access via /mcp.sfmc.writeAmpscript etc. in VS Code, or via the prompts API:

Writing effective prompts

Automatic tool use

Clients that honour the MCP instructions field (Cursor, Claude Desktop, GitHub Copilot Agent mode) will call search_mce_help automatically whenever you ask an MCE administration or setup question — no special phrasing needed. If your client does not process server instructions, or if you want explicit control, the templates below help.

Quick reference: which tool or prompt to use

Copy-paste prompt templates

Classic Engagement admin (most common)

Search the Marketing Cloud Engagement help (product_focus: engagement) and tell me:
<your question here>

Cite which product version your steps apply to and note if the bundled docs are incomplete.

Marketing Cloud Next

Search the Marketing Cloud Next help (product_focus: next) and tell me:
<your question here>

Confirm the steps apply to Marketing Cloud Next, not classic Engagement.

Unknown product / migration question

Search both Marketing Cloud Engagement and Next help (product_focus: any) and tell me:
<your question here>

Separate the steps for classic Engagement vs Marketing Cloud Next clearly.

Explicit use of the answerMceHowTo prompt

In clients that support MCP prompts (e.g. VS Code with the /mcp.sfmc.answerMceHowTo command):

/mcp.sfmc.answerMceHowTo
  question: "How do I create a child business unit and assign it a sender profile?"
  assumeProduct: engagement

Combining MCE admin with code

1. Use search_mce_help (product_focus: engagement) to find the correct Journey Builder entry event
   configuration steps, then
2. Write the AMPscript snippet that reads the data extension row inside the journey email.

What to expect from the AI

• The AI cites the product scope (Engagement or Next) in every answer.
• If the bundled excerpts do not cover the question fully, the AI says so and suggests verifying in the live Salesforce Help.
• Function signatures (AMPscript / SSJS) are always sourced from the language catalog, not from training data.

Refresh bundled Marketing Cloud Engagement help

The published npm package includes bundled/mce-help/chunks.json, produced by npm run bundle-mce-help. By default the bundler uses the path in MCE_HELP_DOCS (see scripts/bundle-mce-help.mjs); set it to the root of your mirrored MCE Help Markdown tree when not using the maintainer default.

cd mcp-server-sfmc
npm run bundle-mce-help
npm run build
npm test

Example: MCE_HELP_DOCS=/absolute/path/to/mce-help-mirror npm run bundle-mce-help

AI code review in pull requests

GitHub Copilot (cloud agent)

The .github/agents/sfmc-reviewer.agent.md custom agent in this repository configures a GitHub Copilot cloud agent that uses mcp-server-sfmc for SFMC-aware PR reviews.

To enable it in your own repository:

1. Copy .github/agents/sfmc-reviewer.agent.md to your repo.
2. In your GitHub repo settings → Copilot → Cloud agent → MCP configuration, add:

{
  "mcpServers": {
    "sfmc": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"],
      "tools": ["*"]
    }
  }
}

1. Assign the sfmc-reviewer agent to a pull request by mentioning it in a comment or via the @sfmc-reviewer agent in GitHub Copilot Chat.

GitHub Copilot (dedicated PR review)

Copy .github/copilot-instructions.md from this repo to your project. GitHub Copilot's dedicated PR review feature reads this file and applies the SFMC language rules when summarising your PRs.

GitLab Duo

1. Copy the content of ci-templates/gitlab-duo-review-instructions.md to .gitlab/duo-instructions.md in your repository.
2. GitLab Duo Code Review will apply these instructions on every merge request.

GitLab Duo's dedicated MR review does not support MCP directly. Use the CI lint job below for automated static analysis, and the Duo instructions for AI-assisted review comments.

CI linting (deterministic checks)

For deterministic, blocking CI validation, use the eslint-plugin-sfmc templates provided in ci-templates/:

These templates run eslint-plugin-sfmc on changed files and post lint results as PR/MR comments.

ESLint + @eslint/mcp

For AI assistants that don't support MCP but do support tool-calling, you can combine eslint-plugin-sfmc with the official @eslint/mcp server. Add it alongside mcp-server-sfmc:

{
  "servers": {
    "sfmc": {
      "command": "npx",
      "args": ["-y", "mcp-server-sfmc@latest"]
    },
    "eslint": {
      "command": "npx",
      "args": ["-y", "@eslint/mcp@latest"]
    }
  }
}

Create an eslint.config.mjs in your project root:

import sfmc from 'eslint-plugin-sfmc';
export default [...sfmc.configs.recommended];

The @eslint/mcp server exposes an eslint_lint tool that your AI can call to run the full ESLint rule set (including all AMPscript and SSJS rules from eslint-plugin-sfmc) on any file.

Architecture

mcp-server-sfmc
    └── sfmc-language-lsp   (language intelligence core)
            ├── ampscript-data  (AMPscript function catalog)
            └── ssjs-data       (SSJS function catalog)

vscode-sfmc-language (VS Code extension)
    └── sfmc-language-lsp   (same core, bundled via esbuild)

Both the VS Code extension and the MCP server share exactly the same validation, completion, hover, and lookup logic through sfmc-language-lsp. This means the AI assistant sees the same errors and suggestions that the editor shows.

Contributing

See CONTRIBUTING.md.

License

MIT — see LICENSE.