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  1. Home
  2. πŸ‘€ Customer Data Platforms
  3. Kodey AI Salesforce MCP
Kodey AI Salesforce MCP logo
Health: ActiveRecent health check succeeded.Last checked 10/12/2026, 5:31:41 AM

Kodey AI Salesforce MCP

InstallableWe know how to install it, but have not yet seen it complete a handshake. User RatingsBe the first to rate and review this MCP server!
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salesforcecrmdeveloper-toolsmetadataapex

Connects AI clients to Salesforce orgs for org inspection, record access, metadata deployment, retrieval, and Apex review.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "kodey-ai-salesforce-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@salesforce/mcp"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ‘€ More in Customer Data Platforms

Overview

kodey-ai-salesforce-mcp MCP server connects MCP-compatible clients to authorized Salesforce orgs through Salesforce TypeScript libraries. It can list orgs, inspect records, deploy or retrieve metadata, and support Apex code and rule analysis through configured toolsets. Access is controlled with an org allowlist, while authentication uses existing encrypted Salesforce authorization files rather than secrets in server configuration. Reach for it when an agent needs to perform Salesforce DX workflows from VS Code, Cursor, Cline, Claude Desktop, Zed, or Windsurf.

Use cases

β€’List authorized Salesforce orgs
β€’Inspect records in a Salesforce org
β€’Deploy project metadata to an org
β€’Retrieve Salesforce metadata
β€’Review Apex code and PMD violations

Key features

β€’Salesforce org access over MCP
β€’Org allowlisting
β€’Record inspection
β€’Metadata deployment and retrieval
β€’Apex and PMD analysis
β€’Encrypted local auth-file access

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Kodey AI Salesforce MCP.

Extracted Tool Capabilities
Salesforce org access over MCP
Org allowlisting
Record inspection
Metadata deployment and retrieval
Apex and PMD analysis
Encrypted local auth-file access

How Kodey AI Salesforce MCP works

What kodey-ai-salesforce-mcp MCP server does

kodey-ai-salesforce-mcp MCP server provides an MCP interface for working with Salesforce orgs. It is intended for agent-assisted Salesforce DX tasks, including finding authorized orgs, checking scratch-org status, viewing org records, and working with project metadata.

The documented examples also cover deploying a project to an org, retrieving metadata, reviewing Apex code for possible performance or security problems, and explaining PMD rules such as ApexCRUDViolation. The repository describes the implementation as a developer preview, so its commands, parameters, and available tools may change.

How it works

The server runs as a local stdio process. A client starts it with npx and passes startup flags that determine which Salesforce orgs it may access and which toolsets or individual tools are enabled. The example configuration uses the @salesforce/mcp package and supplies an org alias through --orgs.

Authentication is based on authorization data already stored on the user's computer by Salesforce tooling. The server uses TypeScript libraries directly instead of invoking the Salesforce CLI as a shell command. It passes usernames rather than access tokens through MCP tools and restricts access to explicitly allowed orgs.

Setup and configuration

Before configuring the server, the documented setup expects Salesforce CLI, VS Code, a Salesforce DX project, and at least one authorized Salesforce org. A scratch org can also be used.

For VS Code, add a .vscode/mcp.json file in the DX project, or configure the server globally in VS Code settings. A representative configuration starts the package over stdio and includes:

  • --orgs to define the authorized orgs the server can use.
  • --toolsets to select a group of tools.
  • --tools to select individual tools when finer control is needed.
  • --allow-non-ga-tools when access to non-generally-available tools is required by the configuration.

The README also documents installation through Smithery with the @kodey-ai/salesforce-mcp-kodey package. Agentforce for Developers includes the Salesforce DX MCP server preconfigured in its VS Code extension.

Tools and capabilities

Configured capabilities support several Salesforce development workflows:

  • List authorized Salesforce orgs.
  • Identify active scratch orgs.
  • Query or view org records.
  • Deploy project content to an org.
  • Retrieve metadata from an org.
  • Review Apex code for performance or security concerns.
  • Explain PMD rule violations.

The exact tools available depend on the selected toolsets and flags. The documented examples show natural-language requests being routed to the appropriate configured tool, with the client presenting the action and its results.

Limitations and notes

kodey-ai-salesforce-mcp MCP server is marked as a developer preview. The README warns that functionality, commands, parameters, and tools can change or be deprecated without notice, and advises against implementing dependent functionality around the preview commands.

The --orgs option is required in the documented VS Code setup. Only explicitly allowlisted orgs are available to the server. This project should therefore be evaluated with those preview status and access-control requirements in mind before being used in a stable automation workflow.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

npm downloads
151k
Package downloads in the last 30 days.
Last commit
11mo ago
Most recent push to the default branch.

Reviews

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Frequently Asked Questions about Kodey AI Salesforce MCP

kodey-ai-salesforce-mcp is an MCP server that connects AI clients to authorized Salesforce orgs. Its documented tools support listing orgs, inspecting records, deploying and retrieving metadata, and reviewing Apex code or PMD violations. It runs locally over stdio and uses existing encrypted Salesforce authorization files instead of exposing tokens.

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Technical Specs & Signals

CategoryπŸ‘€Customer Data Platforms
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
LicenseApache-2.0
ClientsVS Code (GitHub Copilot), Cursor, Cline / VS Code, Claude Desktop, Zed, Windsurf
Last updatedOct 7, 2026
14/14 checks healthy over the last 64d
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit11mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Oct 24, 2025
npm downloads151,402/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
40Quality signal: Fair Β· 40/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

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Critical 0High 0Medium 0Low 0

Scanned 8d ago via OSV.dev Β· @salesforce/mcp (npm)

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