Tango MCP connector for AI agents

CALL ANY TOOL

8 tools covering create, publish, get.

tangomcp_fetch_api_docs

Fetch detailed tango api documentation for a specific sectio

Fetch detailed tango api documentation for a specific section. use when you need the full list of filtering parameters, valid enum values, ordering options, response shaping syntax, or advanced query patterns beyond what the tool descriptions provide.

Parameters

Name

Type

Required

Description

section

string

Required

Documentation section to retrieve. Valid values: 'budget_accounts', 'contracts', 'entities', 'forecasts', 'gsa-elibrary', 'idvs', 'itdashboard', 'lcats', 'metrics', 'opportunities', 'otas', 'otidvs', 'protests', 'resolve', 'response-shaping', 'subawards', 'vehicles'.

tangomcp_get_details

Get detailed information about a single item — entity, contr

tangomcp_resolve

Find entities, vehicles, naics/psc codes, gsa mas sins, cont

tangomcp_search

Search contracts, idvs, vehicles, gsa elibrary schedule hold

tangomcp_search_opportunities

Search open federal procurement opportunities and forecasts.

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="tangomcp")

mcp = MultiServerMCPClient({
    "tangomcp": {
        "url": "https://mcp.scalekit.com/tangomcp",
        "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: "tangomcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/tangomcp
// 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: "tangomcp" });

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

Try these prompts

Paste any prompt into your agent to get started.

Get started

Copy the prompt

Copied

Search open federal procurement opportunities and forecasts?

Copy the prompt

Copied

Find entities, vehicles, NAICS/PSC codes, GSA MAS SINs, contracts, opportunities, IDVs, OTAs, subawards, organizations, ?

Advanced

Copy the prompt

Copied

Get detailed information about a single item — entity, contract, IDV, vehicle, opportunity, OTA, OTIDV, organization, pr?

Copy the prompt

Copied

Fetch detailed Tango API documentation for a specific section?

SEE HOW AUTH WORKS

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

1

Authorize

Your user connects

Tango 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

Tango 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

Tango 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

Tango 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 Tango 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 Tango 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 Tango?
Yes. Pass a tool name filter to listScopedTools so the research agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Tango.

What happens when a user revokes Tango 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 federal contract search data scoped per user?
Yes. Searches for opportunities, vehicles, and protests run with the authorizing user's Tango credential, so saved views and rate limits stay per analyst, never pooled.

Tango MCP

Tango MCP tools for AI agents