Custom-built MCP Server for Salesforce

说明与用途

自托管的 MCP 服务器使 AI 代理能够通过标准化命令执行 Salesforce 的 CRUD、查询等操作，支持 OAuth PKCE 或客户端凭证身份验证。

问题

Enable AI agents to query, search, and modify Salesforce data via a self-hosted MCP server.

结果

The server enables AI agents to perform Salesforce CRUD, query, bulk, and custom API operations via MCP commands, with optional authentication flows and retry logic.

工作流

• Set up a Salesforce org with an External Client App and obtain Consumer Key
• Choose a deployment option: Option A (uvx), Option B (Python from source), or Option C (Docker)
• Configure environment variables SF_LOGIN_URL and SF_CLIENT_ID (and optionally SF_CLIENT_SECRET, SF_AUTH_FLOW, SF_PKCE_TOKEN_CACHE)
• Run one-time interactive login with sf-mcp-login (or use client credentials flow)
• Start the server with sf-mcp-server (or docker run)
• Configure an MCP client (e.g., Claude Desktop) to use the server command and env vars
• Use MCP tools like sf_query, sf_create_record, etc. to interact with Salesforce

证据

A custom-built, self-hosted MCP server that lets AI agents (Claude Desktop, Claude Code, the MCP Inspector, or any other MCP client) connect to Salesforce — to query, search, and modify data in an org.

来源

Three ways to get a running server — pick whichever fits: Option A — uvx, Option B — Python from source, Option C — Docker

来源

The server also runs as a container behind a network-reachable Streamable HTTP endpoint, for when you want an agent that isn't on the same machine to reach it.

来源