Salesforce MCP Server
A customizable MCP server for integrating Salesforce APIs with GenAI applications, supporting SOQL queries, record CRUD, metadata access, and more.
README
Salesforce MCP Server
<div align="center">
Salesforce Mcp Server
</div>
A highly customizable Model Context Protocol (MCP) server for integrating Salesforce APIs with GenAI applications.
Features
-
Comprehensive Salesforce API Coverage:
- SOQL queries with automatic pagination support
- SOSL (Salesforce Object Search Language) searches
- Record CRUD operations (Create, Read, Update, Delete)
- Metadata API access for object descriptions
- Bulk API operations for large data volumes
- Apex code execution capabilities
- Reports API with filtering support
- Organization limits and API usage monitoring
-
Flexible Authentication:
- OAuth 2.0 Web Server Flow
- OAuth 2.0 JWT Bearer Flow
- Username-Password Flow
- Connected App support
-
Enterprise-Ready:
- Multi-org support
- Rate limiting and retry logic
- Comprehensive error handling
- Audit logging
- Field-level security respect
Installation
pip install salesforce-mcp-server
Or install from source:
git clone https://github.com/asklokesh/salesforce-mcp-server.git
cd salesforce-mcp-server
pip install -e .
Configuration
Create a .env file or set environment variables:
# Salesforce Credentials
SALESFORCE_USERNAME=your_username@company.com
SALESFORCE_PASSWORD=your_password
SALESFORCE_SECURITY_TOKEN=your_security_token
SALESFORCE_DOMAIN=login # or test, or your custom domain
# OR use OAuth
SALESFORCE_CLIENT_ID=your_connected_app_client_id
SALESFORCE_CLIENT_SECRET=your_connected_app_client_secret
SALESFORCE_REDIRECT_URI=http://localhost:8080/callback
# Optional Settings
SALESFORCE_API_VERSION=59.0
SALESFORCE_SANDBOX=false
SALESFORCE_MAX_RETRIES=3
SALESFORCE_TIMEOUT=30
Requirements
- Python 3.10 or newer
- MCP SDK 1.27+
Quick Start
Run the server
The server is built on the MCP Python SDK's FastMCP API and speaks the stdio transport. Install the package, configure credentials via environment variables (see Configuration), and launch with:
salesforce-mcp
# or equivalently
python -m salesforce_mcp.server
Programmatic usage
from salesforce_mcp import mcp
# `mcp` is a configured `FastMCP` instance with every Salesforce tool
# already registered. Run it over stdio:
if __name__ == "__main__":
mcp.run(transport="stdio")
Claude Desktop Configuration
Add to your Claude Desktop config:
{
"mcpServers": {
"salesforce": {
"command": "salesforce-mcp",
"env": {
"SALESFORCE_USERNAME": "your_username@company.com",
"SALESFORCE_PASSWORD": "your_password",
"SALESFORCE_SECURITY_TOKEN": "your_security_token"
}
}
}
}
Available Tools
1. Query Records
Execute SOQL queries to retrieve data:
{
"tool": "salesforce_query",
"arguments": {
"query": "SELECT Id, Name, Email FROM Contact WHERE LastModifiedDate = TODAY",
"include_deleted": false
}
}
2. Get Record
Retrieve a specific record by ID:
{
"tool": "salesforce_get_record",
"arguments": {
"object_type": "Account",
"record_id": "001XX000003DHPh",
"fields": ["Name", "Industry", "AnnualRevenue"]
}
}
3. Create Record
Create new records:
{
"tool": "salesforce_create_record",
"arguments": {
"object_type": "Contact",
"data": {
"FirstName": "John",
"LastName": "Doe",
"Email": "john.doe@example.com",
"AccountId": "001XX000003DHPh"
}
}
}
4. Update Record
Update existing records:
{
"tool": "salesforce_update_record",
"arguments": {
"object_type": "Contact",
"record_id": "003XX000004TMM2",
"data": {
"Title": "Senior Developer",
"Department": "Engineering"
}
}
}
5. Delete Record
Delete records:
{
"tool": "salesforce_delete_record",
"arguments": {
"object_type": "Contact",
"record_id": "003XX000004TMM2"
}
}
6. Describe Object
Get metadata about Salesforce objects:
{
"tool": "salesforce_describe_object",
"arguments": {
"object_type": "Account"
}
}
7. Bulk Operations
Handle large data volumes:
{
"tool": "salesforce_bulk_create",
"arguments": {
"object_type": "Contact",
"records": [
{"FirstName": "Jane", "LastName": "Smith", "Email": "jane@example.com"},
{"FirstName": "Bob", "LastName": "Johnson", "Email": "bob@example.com"}
],
"batch_size": 200
}
}
8. Execute Apex
Run Apex code:
{
"tool": "salesforce_execute_apex",
"arguments": {
"apex_body": "System.debug('Hello from Apex!');"
}
}
9. Search Records (SOSL)
Search across multiple objects:
{
"tool": "salesforce_search",
"arguments": {
"search_query": "FIND {John} IN NAME FIELDS RETURNING Contact(Id, Name, Email), Account(Id, Name)"
}
}
10. Query Pagination
Handle large query results:
{
"tool": "salesforce_query_more",
"arguments": {
"next_records_url": "/services/data/v59.0/query/01gxx000000002ABC-2000"
}
}
11. Organization Limits
Get API limits and usage:
{
"tool": "salesforce_limits",
"arguments": {}
}
12. Run Reports
Execute Salesforce reports:
{
"tool": "salesforce_run_report",
"arguments": {
"report_id": "00O1i000004Gzr0EAC",
"filters": {
"reportMetadata": {
"reportFilters": [
{
"column": "CREATED_DATE",
"operator": "greaterThan",
"value": "2023-01-01"
}
]
}
}
}
}
Advanced Configuration
Multi-Org Support
Additional orgs are configured by setting prefixed environment variables.
For example, to expose a sandbox org alongside the default:
SALESFORCE_USERNAME=prod@company.com
SALESFORCE_PASSWORD=prod_password
SALESFORCE_SECURITY_TOKEN=prod_token
SALESFORCE_SANDBOX_USERNAME=sandbox@company.com.sandbox
SALESFORCE_SANDBOX_PASSWORD=sandbox_password
SALESFORCE_SANDBOX_SECURITY_TOKEN=sandbox_token
SALESFORCE_SANDBOX_DOMAIN=test
Every tool accepts an optional org argument; omitting it targets the
default org defined by SALESFORCE_DEFAULT_ORG (defaulting to "default").
Authentication classes
The salesforce_mcp.auth module exposes UsernamePasswordAuth, OAuth2Auth,
and JWTAuth for use when embedding the underlying SalesforceClient in
your own code:
from salesforce_mcp import JWTAuth, SalesforceClient
auth = JWTAuth(
client_id="your_client_id",
username="your_username",
private_key_file="path/to/private_key.pem",
sandbox=False,
)
client = SalesforceClient(auth=auth)
Rate Limiting
Rate limiting is enabled by default and tuned via environment variables:
SALESFORCE_RATE_LIMIT_ENABLED=true
SALESFORCE_RATE_LIMIT_REQUESTS_PER_SECOND=10
SALESFORCE_RATE_LIMIT_BURST_SIZE=20
Integration Examples
See the examples/ directory for complete integration examples:
basic_usage.py- Simple queries and CRUD operationsbulk_operations.py- Handling large data volumesgenai_integration.py- Integration with GenAI APIsmulti_org.py- Managing multiple Salesforce orgsoauth_flow.py- OAuth authentication setup
Error Handling
The server provides detailed error information:
try:
result = server.execute_tool("salesforce_query", {
"query": "SELECT InvalidField FROM Account"
})
except SalesforceError as e:
print(f"Salesforce error: {e.error_code} - {e.message}")
print(f"Fields available: {e.available_fields}")
Security Best Practices
- Never commit credentials - Use environment variables or secure vaults
- Use OAuth when possible - More secure than username/password
- Implement field-level security - Respect Salesforce permissions
- Enable audit logging - Track all API operations
- Use IP restrictions - Limit access to known IP ranges
Contributing
Contributions are welcome! Please read our contributing guidelines and submit pull requests.
License
MIT License - see LICENSE file for details
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。