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.
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.
From mapping your org to a monitored service in production.
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.
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.
Writes that touch revenue-critical records can require a human confirmation step, so the AI drafts and a person approves before anything is saved.
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.
One governed surface for every AI client, instead of a new integration each time.
Any MCP-capable AI (Claude, ChatGPT, Cursor, your own agents) uses the same server. You build the Salesforce connection once.
Every tool call runs inside your Salesforce permission model. The AI can only see and change what the acting user already could.
Combine Salesforce with your other MCP tools (HubSpot, Pipedrive, your ERP) so an agent can work across systems in a single flow.
We already run a couple hundred MCP tools in production. Auth, rate limits, logging, and error handling are built in from the start.
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.
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.
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.
Yes. We build 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.
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.
We design, build, host, and run it as a managed service. You get a live, monitored server, not a proof of concept to maintain yourself.
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.
