Salesforce Object MCP Server

Salesforce Object MCP Server

Enables AI agents to explore Salesforce metadata by parsing object and field definitions, reducing hallucination when working with Salesforce repositories.

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README

Salesforce Object MCP Server

A Model Context Protocol (MCP) server that helps AI agents understand Salesforce metadata by parsing .object-meta.xml and .field-meta.xml files. This server provides tools for discovering objects, fields, relationships, formulas, and validation rules to reduce AI hallucination when working with Salesforce repositories.

Features

  • Universal Repository Support: Works with any Salesforce repository structure - no configuration needed
  • Automatic Discovery: Recursively finds all .object-meta.xml and .field-meta.xml files
  • Comprehensive Object Information: Access object metadata, fields, relationships, and validation rules
  • Smart Caching: In-memory caching with file modification time checks for fast responses
  • Relationship Mapping: Bidirectional relationship discovery (both incoming and outgoing)
  • Formula & Validation Support: Parse and understand formula fields and validation rules
  • Search Capabilities: Full-text search across all metadata

Available Tools

1. list_objects

List all Salesforce objects in the repository.

Parameters:

  • includeStandard (optional): Include standard objects (default: true)
  • pattern (optional): Filter by name pattern (case-insensitive)

Example:

{
  "includeStandard": false,
  "pattern": "Account"
}

2. get_object_details

Get comprehensive details about a specific object.

Parameters:

  • objectName (required): API name of the object

Example:

{
  "objectName": "Account"
}

3. list_fields

List all fields for a specific object.

Parameters:

  • objectName (required): API name of the object
  • fieldType (optional): Filter by field type (Text, Lookup, Formula, etc.)

Example:

{
  "objectName": "Account",
  "fieldType": "Formula"
}

4. get_field_details

Get detailed information about a specific field.

Parameters:

  • objectName (required): API name of the object
  • fieldName (required): API name of the field

Example:

{
  "objectName": "Account",
  "fieldName": "AnnualRevenue"
}

5. find_relationships

Find all relationships for an object.

Parameters:

  • objectName (required): API name of the object
  • direction (optional): "outgoing", "incoming", or "both" (default: both)

Example:

{
  "objectName": "Contact",
  "direction": "both"
}

6. search_metadata

Search across all metadata by keyword.

Parameters:

  • query (required): Search term (case-insensitive)
  • scope (optional): "objects", "fields", or "all" (default: all)

Example:

{
  "query": "revenue",
  "scope": "fields"
}

7. get_validation_rules

Get validation rules for an object.

Parameters:

  • objectName (required): API name of the object

Example:

{
  "objectName": "Opportunity"
}

Installation

Local Development

  1. Clone the repository:
git clone <repository-url>
cd SFObjectMCP
  1. Install dependencies:
npm install
  1. Build the project:
npm run build
  1. Run the server:
SF_REPO_PATH=/path/to/your/salesforce/repo npm start

Docker

  1. Build the Docker image:
docker build -t sf-object-mcp .
  1. Run the container:
docker run -it \
  -e SF_REPO_PATH=/workspace \
  -v /path/to/your/salesforce/repo:/workspace:ro \
  sf-object-mcp

Docker Compose

  1. Edit docker-compose.yml and update the volume mount:
volumes:
  - /path/to/your/salesforce/repo:/workspace:ro
  1. Start the server:
docker-compose up

MCP Configuration

To use this server with an MCP client (like Claude Desktop), add the following to your MCP configuration file:

Using Local Installation

{
  "mcpServers": {
    "salesforce-metadata": {
      "command": "node",
      "args": ["/path/to/SFObjectMCP/dist/index.js"],
      "env": {
        "SF_REPO_PATH": "/path/to/your/salesforce/repo"
      }
    }
  }
}

Using Docker

{
  "mcpServers": {
    "salesforce-metadata": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SF_REPO_PATH=/workspace",
        "-v",
        "/path/to/your/salesforce/repo:/workspace:ro",
        "sf-object-mcp"
      ]
    }
  }
}

Supported Formats

This server works with any Salesforce repository structure. It scans for .object-meta.xml and .field-meta.xml files anywhere in your repository, regardless of directory structure.

Examples of Supported Structures

Standard SFDX:

force-app/main/default/objects/Account/Account.object-meta.xml

Custom SFDX:

src-package/main/default/core/objects/Account/Account.object-meta.xml

Metadata API:

src/objects/Account.object

Any custom structure:

any-directory/objects/Account/Account.object-meta.xml

The scanner automatically finds all Salesforce metadata files regardless of where they're located in your repository structure.

How It Works

  1. First Tool Call: When the first tool is called, the server scans the repository for all .object-meta.xml and .field-meta.xml files
  2. Parsing: XML files are parsed and converted into structured TypeScript objects
  3. Caching: Parsed metadata is cached in memory with file modification time tracking
  4. Relationship Mapping: The server builds a bidirectional relationship map
  5. Subsequent Calls: Future tool calls use the cache for fast responses

Development

Build

npm run build

Watch Mode

npm run watch

Development Mode

npm run dev

Troubleshooting

Error: SF_REPO_PATH environment variable is required

Make sure you've set the SF_REPO_PATH environment variable to point to your Salesforce repository.

No objects found

Ensure your repository contains .object-meta.xml files. The scanner searches the entire repository recursively, so metadata files can be in any directory structure. Common locations include:

  • force-app/main/default/objects/
  • src-package/main/default/core/objects/
  • src/objects/
  • Any custom directory containing an objects/ folder

Object/Field not found

The server only discovers objects and fields that have metadata files in the repository. Standard objects may not be present unless they've been customized.

Use Cases

  • AI-Assisted Development: Help AI agents understand your Salesforce schema to provide accurate code suggestions
  • Documentation: Generate documentation from metadata
  • Schema Analysis: Understand relationships and dependencies
  • Code Review: Validate field references and formula syntax
  • Migration Planning: Map object and field usage

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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