The LILT MCP connector routes your AI agent's tool calls to LILT's own MCP server through Scalekit. Each user signs in to LILT once, and Scalekit stores and refreshes their tokens, so your agent never handles credentials. It comes with 9 tools.
- Tools
- 9
- What they doRead · write · destructive
- 5 · 4 · 05 read4 write0 destructive
- Users sign in with
- OAuth
- OAuth app
- Scalekit's or your own
Setup
Install the SDK
Terminal window npm install @scalekit-sdk/node dotenvTerminal window pip install scalekit-sdk-python python-dotenvSet your credentials
Add your Scalekit credentials to your
.envfile. Find values in app.scalekit.com > Developers > API Credentials..env SCALEKIT_ENVIRONMENT_URL=<your-environment-url>SCALEKIT_CLIENT_ID=<your-client-id>SCALEKIT_CLIENT_SECRET=<your-client-secret>Create the LILT MCP connection
In AgentKit > Connections, create a LILT MCP connection. The name you give it is the
connection_nameyour code passes. See Configure connections.Scalekit credentials are available for LILT MCP server, so you don't need to register an OAuth app.
Authorize a user and make your first call
quickstart.mts import { ScalekitClient } from '@scalekit-sdk/node'import 'dotenv/config'import { createInterface } from 'node:readline/promises'const scalekit = new ScalekitClient(process.env.SCALEKIT_ENVIRONMENT_URL,process.env.SCALEKIT_CLIENT_ID,process.env.SCALEKIT_CLIENT_SECRET,)const actions = scalekit.actionsconst connector = 'liltmcp'const identifier = 'user_123'// Generate an authorization link for the userconst { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })console.log('Authorize LILT MCP:', link)const rl = createInterface({ input: process.stdin, output: process.stdout })await rl.question('Press Enter after authorizing...')rl.close()// Make your first callconst result = await actions.executeTool({connector,identifier,toolName: 'liltmcp_get_credit_balance_information',toolInput: {},})console.log(result)Terminal window npx tsx quickstart.mtsquickstart.py import osfrom scalekit import ScalekitClientfrom dotenv import load_dotenvload_dotenv()scalekit_client = ScalekitClient(env_url=os.getenv("SCALEKIT_ENVIRONMENT_URL"),client_id=os.getenv("SCALEKIT_CLIENT_ID"),client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),)actions = scalekit_client.actionsconnection_name = "liltmcp"identifier = "user_123"# Generate an authorization link for the userlink_response = actions.get_authorization_link(connection_name=connection_name,identifier=identifier,)print("Authorize LILT MCP:", link_response.link)input("Press Enter after authorizing...")# Make your first callresult = actions.execute_tool(tool_input={},tool_name="liltmcp_get_credit_balance_information",connection_name=connection_name,identifier=identifier,)print(result)Terminal window python quickstart.pyEach user signs in once. See Authorize a user for the full flow and statuses.
Tools
Pass the exact name toexecute_toolliltmcp_check_job_statusChecks the status of a verified translation job.Read-onlyCheck Job Status
Checks the status of a verified translation job.
Inputs
job_idintegerrequired- No description.
liltmcp_download_jobTriggers a job export and returns a download link for the completed translation job.Read-onlyDownload Job
Triggers a job export and returns a download link for the completed translation job.
Inputs
job_idintegerrequired- No description.
liltmcp_get_credit_balance_informationRetrieves all available credit balances for the authenticated user.Read-onlyGet Credit Balance Information
Retrieves all available credit balances for the authenticated user.
Inputs
This tool takes no inputs.
liltmcp_hello_worldReturns a friendly hello world message.Read-onlyHello World
Returns a friendly hello world message. Useful as a connectivity/health check for the Lilt MCP server.
Inputs
This tool takes no inputs.
liltmcp_list_resourcesLists and filters LILT jobs or translation models.Read-onlyList Resources
Lists and filters LILT jobs or translation models.
Inputs
resource_typestringrequired- Type of resource to list. Use "job" for translation jobs or "model" for trained translation models.one of
jobmodel archivedboolean- No description.default
false
liltmcp_create_trained_modelCreates a new trained translation model for a specific language pair.WriteCreate Trained Model
Creates a new trained translation model for a specific language pair.
Inputs
src_langstringrequired- No description.
trg_langstringrequired- No description.
liltmcp_translate_files_with_verificationCreate a verified translation job assigned to professional LILT linguists for file translation.WriteTranslate Files With Verification
Create a verified translation job assigned to professional LILT linguists for file translation.
Inputs
file_idsarrayrequired- No description.
namestringrequired- No description.
src_langstringrequired- No description.
trg_langsarrayrequired- No description.
user_confirmedboolean- No description.default
false
liltmcp_translate_textTranslates text using LILT's instant translate API.WriteTranslate Text
Translates text using LILT's instant translate API.
Inputs
src_langstringrequired- No description.
textstringrequired- No description.
trg_langstringrequired- No description.
liltmcp_upload_fileUpload a file to LILT for translation.WriteUpload File
Upload a file to LILT for translation.
Inputs
contentstringrequired- No description.
namestringrequired- No description.
content_typestring- No description.default
text/plain
No tools match.