Digits MCP connector for AI agents

Digits MCP tools for AI agents

CALL ANY TOOL

10 tools covering financial, dimensional, list.

digitsmcp_dimensional_summarize_transactions

Summarizes transactions and aggregates them into multi-dimen

Summarizes transactions and aggregates them into multi-dimensional summaries. you can use it to receive timeseries data for that is aggregated and bucketed into dimensions (e.g. category, party, time). # important notes - if you are only requesting a time summary, you must provide a filter (such as category id/type, party id/role, etc) - origin is required. origin's "index" is 1 based for interval day, week, month, and quarter; it's the year for interval year. "intervalcount" is the number of lookback intervals. all fields in "origin" must be set. - you must include "time" in the along dimensions when using intervalcount > 1. - when filtering by balance sheet categories (assets, liabilities, equity), you must set aspermanentaccount to true. - always resolve the party / category / department / location using search_term first, then use the ids returned in the filter. - the response may include a "summary" field where the current period amount is zero while prior period is non-zero; do not treat prior amounts as current-period values. - cannot answer questions specific to bills or invoices. do not use expense or income transaction data to approximate bill or invoice amounts.

Parameters

Name

Type

Required

Description

business_id

string

Required

The ID of the business. Use list_businesses to see available IDs.

aggregate_facet_kind

string

Optional

No description.

along

object

Optional

No description.

as_permanent_account

boolean

Optional

No description.

default_category_type

string

Optional

No description.

direction

string

Optional

No description.

digitsmcp_financial_statement

Generate complete financial statements: profit & loss, balan

digitsmcp_list_business_users

List all users with access to a business. requires a busines

digitsmcp_list_businesses

List all businesses (legal entities) the authenticated user

digitsmcp_list_categories

This tool is used to list categories. use this when you need

digitsmcp_list_departments

This tool is used to list departments. use this when you nee

digitsmcp_list_locations

This tool is used to list locations. use this when you need

digitsmcp_query_transactions

Query and filter individual transactions. this tool provide

digitsmcp_search_term

Resolve a customer, vendor, category, department, location n

digitsmcp_select_business

Select a business to work with. after calling this tool, use

Build your Agent

Same auth pattern across every framework.

from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="digitsmcp")

mcp = MultiServerMCPClient({
    "digitsmcp": {
        "url": "https://mcp.scalekit.com/digitsmcp",
        "headers": {"Authorization": "Bearer " + token}
    }
})
tools = await mcp.get_tools()

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

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "digitsmcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/digitsmcp
// Pass: Authorization: Bearer + token

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

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "digitsmcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/digitsmcp
// Pass: Authorization: Bearer + token

from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="digitsmcp")
# Connect to MCP at https://mcp.scalekit.com/digitsmcp
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Get started

Copy the prompt

Copied

Select a business to work with?

Copy the prompt

Copied

Resolve a customer, vendor, category, department, location name or transaction description to its canonical form using f?

Advanced

Copy the prompt

Copied

Query and filter individual transactions?

Copy the prompt

Copied

This tool is used to list locations?

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

Authorize

Your user connects

Digits 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

Store

Their

Digits 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

Resolve

When your agent calls a

Digits 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

Audit

Every

Digits 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

See the same per-user auth pattern across other connectors.

No items found.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought.

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.

// shared token
 audit → bot_service_account

 // scalekit
 audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

One connector today. Ten 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 access Digits as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Digits OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Digits?
Yes. Pass a tool name filter to listScopedTools so the AI agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Digits.

What happens when a user revokes Digits access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Is Digits access really read-only?
Yes. The connector exposes read-only tools for transactions, statements, and categories. Scalekit adds a pre-call scope check on top, so financial data leaves Digits only for authorized readers.

On this page

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