LILT MCP

Live

OAUTH 2.0

AI

AI

LILT is an enterprise translation platform that combines AI speed with human expertise to deliver accurate, domain-specific translations at scale. This...

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
LILT MCP
agent · Acme Q3
Run
Check Job Status in LILT MCP
S
liltmcp_check_job_status
85ms
LILT MCP agent
Checks the status of a verified translation job..
Sources: LILT MCP
liltmcpmcp
1 tool call
18:29
Message Claude...

Tools your agent reaches for on LILT, scoped per user.

CALL ANY TOOL
Translate files with verification, track jobs, and manage trained models on the user's account.
liltmcp_check_job_status
Checks the status of a verified translation job.
Checks the status of a verified translation job.
Parameters
Name
Type
Required
Description
job_id
integer
Required
No description.
liltmcp_create_trained_model
Creates a new trained translation model for a specific langu
liltmcp_download_job
Triggers a job export and returns a download link for the co
liltmcp_get_credit_balance_information
Retrieves all available credit balances for the authenticate
liltmcp_list_resources
Lists and filters lilt jobs or translation models.
liltmcp_translate_files_with_verification
Create a verified translation job assigned to professional l
liltmcp_translate_text
Translates text using lilt's instant translate api.
liltmcp_upload_file
Upload a file to lilt for translation.
Build your Agent
Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.
Python · LlamaIndex
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="liltmcp")

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

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

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/liltmcp
// 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="liltmcp")
# Connect to MCP at https://mcp.scalekit.com/liltmcp
# Pass: Authorization: Bearer + token
Try these prompts
Copy any prompt into your agent. Each maps directly to a LILT tool. Click to copy, paste into your agent, done.
Get started
Copy the prompt
Copied
Upload a file to LILT for translation?
Copy the prompt
Copied
Translates text using LILT’s instant translate API?
Advanced
Copy the prompt
Copied
Create a verified translation job assigned to professional LILT linguists for file translation?
Copy the prompt
Copied
Lists and filters LILT jobs or translation models?
SEE HOW AUTH WORKS
Your users connect once. Their LILT credentials stay vaulted, every call is scope-checked, and every action is logged.
1
Authorize
Your user connects
LILT 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
LILT 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
LILT 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
LILT 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. Scalekit starts with identity, scope enforcement, and audit. Connectors follow.
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 LILT 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 LILT 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 LILT?
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 LILT.

What happens when a user revokes LILT 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.

Whose translation memory and credits does LILT use?
The authorizing user's LILT account. File translations, trained models, and job downloads draw on that organization's resources and credit balance, keeping enterprise translation governed.

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
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""liltmcp"": {
""url"": ""https://mcp.scalekit.com/liltmcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.liltmcp]
url = ""https://mcp.scalekit.com/liltmcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""liltmcp"": {
""url"": ""https://mcp.scalekit.com/liltmcp"",
""type"": ""http""
}
}
}