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.

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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
  └───────────────────────────┘

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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)

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Installation

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

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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 |

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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: ``bash 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"
      }
    }
  }
}

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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

Salesforce AI Agent MCP Server