Revealed AI MCP

CALL ANY TOOL

API key scoped per rep. Every signal query attributed to the authorizing sales team member.

revealed_account_signals_get

Get account signals

Retrieve real-time buying signals for target accounts including page visits, intent spikes, and product research activity.

Parameters

Name

Type

Required

Description

domain

string

Optional

Company domain to get signals for

account_id

string

Optional

Revealed AI account ID

days

integer

Optional

Lookback window in days (default 7)

revealed_visitors_identify

Identify visitors

revealed_accounts_search

Search accounts

revealed_contacts_get

Get contacts

revealed_intent_trends_get

Get intent trends

Build your Agent

Drop the toolkit in, point it at the authorized sales rep, and your agent can access Revealed AI buyer intent and account intelligence from the first run.

Copied

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

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

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["apollomcp"], toolNames: ["apollo_contacts_search", "apollo_people_enrich", "apollo_sequences_add"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

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

Copied

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: ["apollomcp"], toolNames: ["apollo_contacts_search", "apollo_people_enrich", "apollo_sequences_add"] },
  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: ["apollomcp"], toolNames: ["apollo_contacts_search", "apollo_people_enrich", "apollo_sequences_add"] },
  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 }],
});

Copied

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/apollomcp",
    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 sales intelligence agent to start pulling buyer intent data from Revealed AI.

Search & recall

Copy the prompt

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Show accounts showing high intent for [product category] in the last 7 days.

Copy the prompt

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Find accounts in my territory with intent spikes on [competitor name] this week.

Copy the prompt

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Get the full intent signal history for [account name] over the past 30 days.

Prioritize & act

Copy the prompt

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Rank my top 20 open opportunities by current intent score and suggest outreach order.

Copy the prompt

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List all accounts showing intent but not yet in any active sequence.

Copy the prompt

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Which formerly active accounts have re-emerged with new intent signals this month?

SEE HOW AUTH WORKS

Sales reps authorize Revealed AI once. Their API key stays vaulted, every intent query is scoped to their account permissions, and every access is logged.

1

Authorize

Your user connects

Revealed AI MCP

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:

Limited to user

2

Store

Their

Revealed AI MCP

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

3

Resolve

When your agent calls a

Revealed AI MCP

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

4

Audit

Every

Revealed AI MCP

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

Same per-user auth pattern across other sales intelligence and intent data connectors.

No items found.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

One vault for every sales signal connector. Revealed AI today, Gong and Apollo tomorrow.

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.

Revealed AI MCP today. Others tomorrow.

“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

FAQs

Frequently Asked Questions

Does the agent use a shared Revealed AI key or per-user keys?

Per-user keys. Each sales rep provisions their Revealed AI API key and Scalekit vaults it under their identity. Signal queries are attributed to that rep, not a shared team credential.

Where is the Revealed AI API key stored?

In Scalekit's AES-256 vault, namespaced per tenant. Keys resolve at request time and never appear in prompts, logs, or LLM completions.

Can I limit which accounts a rep's agent can query signals for?

Yes. Use listScopedTools to restrict signal queries to a rep's assigned territory or account list, preventing cross-territory data access between reps.

What happens when a rep's Revealed AI key is revoked?

The next tool call fails closed for that rep. Other users in the tenant remain unaffected. Revocation is logged with a timestamp.

Can the agent combine Revealed AI signals with CRM data in one workflow?

Yes. A single agent can call Revealed AI for intent signals and Salesforce or HubSpot for CRM status in the same workflow. Each connector resolves under the same user identity with its own vaulted credential.

Tools your sales agent reaches for on Revealed AI, scoped per rep.