Salesforce connector for AI agents

Tools your Salesforce agent reaches for, scoped per user.

CALL ANY TOOL

Read and write accounts, contacts, leads, opportunities, and cases. Run SOQL queries for custom data retrieval.

salesforce_soql_query

Run SOQL query

Execute an arbitrary Salesforce Object Query Language query for custom data retrieval across any object.

Parameters

Name

Type

Required

Description

query

string

Required

SOQL query string (e.g. SELECT Id, Name FROM Account LIMIT 10)

salesforce_record_search

Search records

salesforce_record_get

Get record

salesforce_record_create

Create record

salesforce_record_update

Update record

salesforce_task_create

Log activity

Build your Agent

Drop the toolkit in, point it at the user, and your agent can query Salesforce records and run SOQL from the first run.

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import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["salesforce"], toolNames: ["salesforce_soql_query", "salesforce_record_search", "salesforce_record_get"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: t.tool.definition.input_schema,
  func: async (args) => sk.tools.executeTool({
    toolName: t.tool.definition.name, identifier: "user_123", toolInput: args,
  }),
}));

const agent = createReactAgent({ llm, tools: lcTools });

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import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["salesforce"], toolNames: ["salesforce_soql_query", "salesforce_record_search", "salesforce_record_get"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["salesforce"], toolNames: ["salesforce_soql_query", "salesforce_record_search", "salesforce_record_get"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

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import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/salesforce",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start pulling CRM intelligence from Salesforce.

Search & recall

Copy the prompt

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Show me all open opportunities over $100K closing this quarter.

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Find all contacts at [account name].

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List all leads from [campaign name].

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What cases are open with priority High?

Action & updates

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Update the stage on [opportunity name] to Negotiation.

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Create a new lead: [name], [company], [email].

Copy the prompt

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Log a call with [contact name]: [notes].

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Close won the [opportunity name] deal at [$amount].

Pipeline & reporting

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Run a SOQL query: SELECT StageName, SUM(Amount) FROM Opportunity GROUP BY StageName.

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What is my total pipeline value this quarter?

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Which accounts have no activity in the last 30 days?

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List all opportunities owned by [rep name].

SEE HOW AUTH WORKS

Users authorize Salesforce once. Their org credentials stay vaulted, every call is checked, and every action is logged.

Authorize

Your user connects

Salesforce

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

A’s meetings only

Store

Their

Salesforce

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Salesforce

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Salesforce

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across HubSpot, Attio, and other CRM connectors.

GTM

Salesforce customer insights agent

Surface Salesforce account activity, NPS signals, and renewal flags into Slack threads for the account team.

Salesforce

Slack

View agent

GTM

CRM AI agent

Log calls, update opportunity stages, and surface stalled deals across HubSpot or Salesforce. No manual data entry.

HubSpot

Salesforce

View agent

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought. Scalekit starts with user identity, scope enforcement, and audit.

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.

// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Salesforce today. Others tomorrow.

Capability

DIY

Scalekit AgentKit

Token storage

Build + maintain yourself

AES-256 vault, managed

Per-user isolation

Custom credential map

Per-tenant namespace, default

Scope enforcement

Manual checks or none

Per-request, pre-API call

Token refresh

Cron job you maintain

Automatic

Audit trail

Build your own logging

90-day, SIEM-exportable

New connector

New OAuth implementation

Same pattern, one config

Multi-framework

Per-framework adapter code

8 adapters included

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit

Start in your coding agent

Up and running in one command

Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up

Claude Code REPL

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/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack

Cursor Code REPL

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# ~/.cursor/mcp.json
{
""mcpServers"": {
""salesforce"": {
""url"": ""https://mcp.scalekit.com/salesforce"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}

Codex Code REPL

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# ~/.codex/config.toml
[mcp_servers.salesforce]
url = ""https://mcp.scalekit.com/salesforce""
auth_env = ""SCALEKIT_TOKEN""

Copilot Code REPL

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# .vscode/mcp.json
{
""servers"": {
""salesforce"": {
""url"": ""https://mcp.scalekit.com/salesforce"",
""type"": ""http""
}
}
}