Salesforce MCP Server

The Salesforce MCP Server bridges the gap between conversational AI assistants and the rich ecosystem of Salesforce data. By exposing a comprehensive set of tools over the Model Context Protocol, it lets Claude (or any MCP‑compatible client) perform complex data operations—querying, updating, and even creating objects—using natural language. This eliminates the need for developers to write SOQL/SOSL, Apex, or REST calls manually, enabling rapid prototyping and efficient data manipulation directly from a chat interface.

At its core, the server offers object and field management capabilities. Developers can instruct the assistant to create new custom objects or add fields, specifying properties such as data type and picklist values. The tool also supports modifying existing objects and fields, automatically handling field‑level security for the System Administrator profile while allowing fine‑grained permission adjustments for other profiles. This feature streamlines the iterative design of Salesforce schemas without leaving the conversational workflow.

For data retrieval, the server implements smart object search and detailed schema introspection. A user can ask for all fields on the Account object or request a list of objects matching a partial name, and the assistant will return structured metadata. Complex queries are supported through dedicated tools that handle parent‑to‑child and child‑to‑parent relationships, as well as advanced WHERE clauses. Aggregate queries with GROUP BY and functions like COUNT or SUM are also available, making it possible to derive business insights on the fly.

Data manipulation is equally powerful. The salesforce_dml_records tool covers insert, update, delete, and upsert operations with external IDs. By phrasing commands in plain English—such as “Update status of multiple accounts”—developers can perform bulk changes without crafting DML statements. Cross‑object search via SOSL is provided through salesforce_search_all, allowing keyword queries that span multiple objects and return field snippets.

Integration into AI workflows is seamless. The server’s tools are stateless, so an assistant can chain them: first describe an object, then query related records, and finally update a field—all within the same conversation. Authentication is flexible; developers can switch between multiple Salesforce orgs based on their VS Code workspace settings, ensuring that the assistant operates in the correct environment without manual re‑login steps.

In summary, the Salesforce MCP Server turns conversational AI into a full‑blown Salesforce developer assistant. It removes boilerplate code, accelerates schema changes, and empowers non‑technical stakeholders to interact with Salesforce data naturally. For teams looking to embed AI into their development pipelines or provide end‑users with instant access to business data, this server delivers a clean, protocol‑driven bridge between language and the Salesforce platform.