Which integrations are available for this server?

Provides tools for managing Jira Cloud stories, including fetching, updating status, posting comments, and searching via JQL. Provides tools for triggering n8n workflows and checking execution status. Provides tools for interacting with Salesforce Tooling and Metadata APIs, including managing custom fields, validation rules, deploying metadata, and querying with SOQL.

How do I use Salesforce AI Agent MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Salesforce AI Agent MCP Server Read Jira story ABC-123 and deploy custom field to Salesforce" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Salesforce AI Agent MCP Server

by pratapsfdc22-dev

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

Salesforce AI Agent MCP Server

A production-grade Model Context Protocol (MCP) server that gives Claude direct, structured access to Jira Cloud, Salesforce (Tooling + Metadata APIs), and n8n workflows.

Built for the Salesforce Developer AI Agent project — an automation pipeline that reads Jira stories, interprets Salesforce configuration requirements, and deploys metadata (custom fields, validation rules, etc.) directly into Salesforce.

Architecture

Claude Desktop / Claude Code / VS Code
           │  (stdio or SSE)
           ▼
  salesforce-ai-agent-mcp
  ┌───────────────────────────┐
  │  Tools (12 total)         │
  │  ├── Jira (4 tools)       │──► Jira Cloud REST API v3
  │  ├── Salesforce (6 tools) │──► Salesforce Tooling + Metadata APIs
  │  └── n8n (2 tools)        │──► n8n Webhook + REST API
  └───────────────────────────┘

Related MCP server: jira-mcp-server

Prerequisites

Node.js ≥ 18
npm ≥ 9
A Jira Cloud account with API token
A Salesforce org with a Connected App (OAuth 2.0)
An n8n instance (optional, for workflow orchestration)

Installation

cd salesforce-ai-agent-mcp
npm install
npm run build

Configuration

Copy .env.example to .env and fill in your credentials:

cp .env.example .env

Jira

Variable	Description
`JIRA_BASE_URL`	e.g. `https://your-org.atlassian.net`
`JIRA_EMAIL`	Your Atlassian account email
`JIRA_API_TOKEN`	Generate at Atlassian API Tokens

Salesforce

You need a Connected App with the Username-Password OAuth flow enabled.

In Salesforce Setup → App Manager → New Connected App
Enable OAuth settings
Add scope: api, refresh_token
Copy Consumer Key → SF_CLIENT_ID
Copy Consumer Secret → SF_CLIENT_SECRET

Variable	Description
`SF_LOGIN_URL`	`https://login.salesforce.com` (prod) or `https://test.salesforce.com` (sandbox)
`SF_CLIENT_ID`	Connected App Consumer Key
`SF_CLIENT_SECRET`	Connected App Consumer Secret
`SF_USERNAME`	Your Salesforce username
`SF_PASSWORD`	Your Salesforce password
`SF_SECURITY_TOKEN`	Reset at Setup → Personal Information → Reset Security Token
`SF_API_VERSION`	API version, e.g. `v61.0` (default)

n8n

Variable	Description
`N8N_BASE_URL`	Your n8n instance URL, e.g. `https://your-n8n.com`
`N8N_API_KEY`	Generate at n8n Settings → API → Create API Key

Usage

stdio mode (Claude Desktop / Claude Code / VS Code)

npm start
# or for development:
npm run dev

SSE mode (for remote/n8n integration)

npm run start:sse
# or for development:
npm run dev:sse

Endpoints available in SSE mode:

GET http://localhost:3000/sse — clients connect here
POST http://localhost:3000/messages?sessionId=<id> — clients send messages here
GET http://localhost:3000/health — liveness probe

Override the port:

MCP_PORT=8080 npm run start:sse

Connecting to Claude Desktop

Add the following to your claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "salesforce-ai-agent": {
      "command": "node",
      "args": ["/absolute/path/to/salesforce-ai-agent-mcp/dist/index.js"],
      "env": {
        "JIRA_BASE_URL": "https://your-org.atlassian.net",
        "JIRA_EMAIL": "you@company.com",
        "JIRA_API_TOKEN": "your_token",
        "SF_LOGIN_URL": "https://login.salesforce.com",
        "SF_CLIENT_ID": "your_client_id",
        "SF_CLIENT_SECRET": "your_client_secret",
        "SF_USERNAME": "you@yourorg.com",
        "SF_PASSWORD": "yourpassword",
        "SF_SECURITY_TOKEN": "yourSecurityToken",
        "N8N_BASE_URL": "https://your-n8n.com",
        "N8N_API_KEY": "your_n8n_api_key"
      }
    }
  }
}

Connecting to Claude Code (VS Code Extension)

Add to your VS Code settings.json (or via the MCP extension UI):

{
  "mcp.servers": {
    "salesforce-ai-agent": {
      "command": "node",
      "args": ["${workspaceFolder}/salesforce-ai-agent-mcp/dist/index.js"],
      "env": {
        "JIRA_BASE_URL": "https://your-org.atlassian.net",
        "JIRA_EMAIL": "you@company.com",
        "JIRA_API_TOKEN": "your_token",
        "SF_LOGIN_URL": "https://login.salesforce.com",
        "SF_CLIENT_ID": "your_client_id",
        "SF_CLIENT_SECRET": "your_client_secret",
        "SF_USERNAME": "you@yourorg.com",
        "SF_PASSWORD": "yourpassword",
        "SF_SECURITY_TOKEN": "yourSecurityToken",
        "N8N_BASE_URL": "https://your-n8n.com",
        "N8N_API_KEY": "your_n8n_api_key"
      }
    }
  }
}

Alternatively, the mcp.json file at the root of this project is compatible with VS Code's MCP extension and will be auto-detected if placed in your workspace root.

Available Tools (12 total)

Jira Tools

`jira_get_story`

Fetch a Jira story by issue key. Returns summary, description, acceptance criteria, status, labels, and all custom fields.

issueKey: "SFDC-123"

`jira_update_story_status`

Transition a Jira story to a new workflow status.

issueKey: "SFDC-123"
targetStatus: "In Progress"   # must match an available transition

`jira_post_comment`

Post a comment to a Jira story (used by the AI agent to report results or ask for clarification).

issueKey: "SFDC-123"
body: "Deployed Customer_Tier__c field to Account. Deployment ID: 0Af..."

`jira_search_stories`

JQL-based story search.

jql: "label = \"sf-config\" AND status = \"To Do\" AND project = SFDC"
maxResults: 25

Salesforce Tools

`salesforce_get_object_fields`

Describe all fields on a Salesforce object.

objectName: "Account"

`salesforce_create_custom_field`

Create a custom field via the Tooling API.

objectName: "Account"
fieldLabel: "Customer Tier"
fieldApiName: "Customer_Tier"     # __c added automatically
fieldType: "Picklist"
picklistValues: ["Platinum", "Gold", "Silver", "Bronze"]
description: "Tier classification for account segmentation"

Lookup field example:

objectName: "Case"
fieldLabel: "Related Contract"
fieldApiName: "Related_Contract"
fieldType: "Lookup"
referenceTo: "Contract"

`salesforce_create_validation_rule`

Create a validation rule via the Tooling API.

objectName: "Account"
ruleName: "Require_Phone_For_Hot_Leads"
errorConditionFormula: "AND(Rating = \"Hot\", ISBLANK(Phone))"
errorMessage: "Phone number is required for Hot-rated accounts"
errorDisplayField: "Phone"
active: true

`salesforce_deploy_metadata`

Trigger a metadata deployment from a base64-encoded ZIP.

zipFile: "<base64-encoded-zip>"
checkOnly: false
testLevel: "RunLocalTests"
rollbackOnError: true

`salesforce_get_deployment_status`

Poll a deployment's status.

deploymentId: "0AfXXXXXXXXXXXXX"

`salesforce_query`

Execute SOQL for validation and verification.

soql: "SELECT Id, Name, Customer_Tier__c FROM Account WHERE Rating = 'Hot' LIMIT 10"

n8n Tools

`n8n_trigger_workflow`

Trigger an n8n workflow via webhook URL.

webhookUrl: "https://your-n8n.com/webhook/abc123"
payload: {
  "issueKey": "SFDC-123",
  "environment": "sandbox",
  "triggeredBy": "claude"
}

`n8n_get_execution_status`

Check the status of an n8n execution.

executionId: "12345"

Example AI Agent Workflow

You: "Process Jira story SFDC-456 and deploy the Salesforce configuration"

Claude:
1. jira_get_story(issueKey: "SFDC-456")
   → reads requirements: "Add Customer_Tier picklist to Account"

2. salesforce_get_object_fields(objectName: "Account")
   → confirms Customer_Tier__c doesn't exist yet

3. salesforce_create_custom_field(
     objectName: "Account",
     fieldLabel: "Customer Tier",
     fieldApiName: "Customer_Tier",
     fieldType: "Picklist",
     picklistValues: ["Platinum", "Gold", "Silver"]
   )
   → creates the field

4. salesforce_query(soql: "SELECT QualifiedApiName FROM FieldDefinition WHERE EntityDefinition.QualifiedApiName = 'Account' AND QualifiedApiName = 'Customer_Tier__c'")
   → verifies the field was created

5. jira_post_comment(
     issueKey: "SFDC-456",
     body: "✅ Customer_Tier__c picklist field created on Account object with values: Platinum, Gold, Silver."
   )

6. jira_update_story_status(issueKey: "SFDC-456", targetStatus: "Done")

Logging

All logs are written as structured JSON to stderr so they never interfere with the MCP stdio transport.

Control the log level via environment variable:

LOG_LEVEL=debug npm start    # debug | info | warn | error

Development

# Type-check only
npm run typecheck

# Build
npm run build

# Dev with hot reload (stdio)
npm run dev

# Dev with hot reload (SSE)
npm run dev:sse

Project Structure

salesforce-ai-agent-mcp/
├── src/
│   ├── index.ts              # Entry point — stdio & SSE transport setup
│   ├── server.ts             # McpServer creation & tool registration
│   ├── tools/
│   │   ├── jira.ts           # Jira tool definitions (4 tools)
│   │   ├── salesforce.ts     # Salesforce tool definitions (6 tools)
│   │   └── n8n.ts            # n8n tool definitions (2 tools)
│   ├── clients/
│   │   ├── jiraClient.ts     # Jira REST API v3 client
│   │   ├── salesforceClient.ts  # Salesforce Tooling/Metadata API + OAuth
│   │   ├── n8nClient.ts      # n8n webhook + REST API client
│   │   └── logger.ts         # Structured JSON logger (stderr)
│   └── types/
│       └── index.ts          # Shared TypeScript types
├── .env.example              # All required environment variables
├── mcp.json                  # VS Code MCP extension manifest
├── package.json
├── tsconfig.json
└── README.md

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