What is a Salesforce MCP server?
A Salesforce MCP server is a Model Context Protocol server that exposes your Salesforce org to AI clients as a set of typed, permissioned tools. Instead of a brittle one-off integration for every assistant, an AI client (Claude, ChatGPT, or your own agent) can query accounts, update opportunities, and log activities through a single governed interface, with every action scoped to what the acting user is allowed to do.
Where it really pays off: complex Salesforce orgs
Off-the-shelf MCP connectors assume a stock Salesforce. Most real orgs aren't: years of custom objects, custom fields, record types, validation rules, and Flows that encode how your business actually works. A generic connector either ignores that layer or trips over it. Because we build your server against your schema, the AI treats your custom objects and processes as first-class tools, respecting the validation and automation you already rely on, instead of writing raw records that break things downstream.
- Custom objects and fields exposed as typed, validated tools
- Record types and validation rules respected, not bypassed
- Your Flows and automations preserved, so writes stay clean
How we build your Salesforce MCP server
From mapping your org to a monitored service in production.
- 1
Map your objects and permissions
We map the Salesforce objects, fields, and record-level permissions that matter, so the server mirrors your org's security model instead of bypassing it.
- 2
Expose typed tools
Each action (find an account, update an opportunity, create a task) becomes a typed MCP tool with validated inputs and outputs, so the AI can't send malformed writes.
- 3
Add review where it counts
Writes that touch revenue-critical records can require a human confirmation step, so the AI drafts and a person approves before anything is saved.
- 4
Host and run it
We deploy the server, monitor it, and keep it current with Salesforce API and MCP spec changes. You get a running service, not a repo to maintain.
Why an MCP server beats a custom integration
One governed surface for every AI client, instead of a new integration each time.
One surface, every client
Any MCP-capable AI (Claude, ChatGPT, Cursor, your own agents) uses the same server. You build the Salesforce connection once.
Permissioned by design
Every tool call runs inside your Salesforce permission model. The AI can only see and change what the acting user already could.
Composable with your stack
Combine Salesforce with your other MCP tools (HubSpot, Pipedrive, your ERP) so an agent can work across systems in a single flow.
Production-grade, not a demo
Reflekt Lab already runs a couple hundred MCP tools in production. Auth, rate limits, logging, and error handling are built in from the start.
What should the AI be allowed to do in Salesforce?
Tell us the objects and the actions you have in mind. We will tell you how we would scope the server and its permissions.
Salesforce MCP server: frequently asked questions
What is a Salesforce MCP server?
It is a Model Context Protocol server that exposes your Salesforce org to AI clients as typed, permissioned tools, so an assistant can read and write Salesforce safely without a custom integration for each AI.
How is an MCP server different from the Salesforce API?
The Salesforce API is the raw interface. An MCP server wraps it into typed, permissioned tools that any AI client can use directly, so you don't build and maintain a separate integration for every assistant.
Can the AI write to Salesforce, or only read?
Both. Reads are direct; writes can be gated behind a human confirmation step for revenue-critical records, so the AI drafts the change and a person approves it.
Does it work with HubSpot or Pipedrive too?
Yes. Reflekt Lab builds MCP servers for Salesforce, HubSpot, Pipedrive, and custom CRMs, and they compose, so one agent can work across several of them in the same flow.
Is our Salesforce data secure?
Every tool call runs inside your Salesforce permission model and is logged. The AI never gets broader access than the acting user, and nothing is stored outside your own systems.
Do you build the MCP server, or just advise?
Reflekt Lab designs, builds, hosts, and runs it as a managed service. You get a live, monitored server, not a proof of concept to maintain yourself.
How do I connect Salesforce to Claude with MCP?
Use Salesforce's hosted MCP servers, generally available since April 2026 on Enterprise Edition and above. Activate a server such as sobject-reads in Setup, create an External Client App with OAuth for Claude, then in Claude open Customize, then Connectors, add a custom connector with the server URL, paste the app's consumer key as the OAuth client ID, and sign in with your Salesforce account. Each user works inside their own Salesforce permissions. You need a custom Salesforce MCP server, which is what Reflekt Lab builds and runs, when the AI must follow your custom objects, record types and Flows, confirm revenue-critical writes, or act across Salesforce and another system. The full steps are in our guide to connecting Salesforce to Claude.
Want AI to work inside your Salesforce, safely?
Tell us your objects and the actions you want AI to take. We'll scope a Salesforce MCP server and show you a working demo.
