The LeadBoxer MCP connector routes your AI agent's tool calls to LeadBoxer's own MCP server through Scalekit. Each user signs in to LeadBoxer once, and Scalekit stores and refreshes their tokens, so your agent never handles credentials. It comes with 5 tools.
- Tools
- 5
- What they doRead · write · destructive
- 4 · 0 · 14 read0 write1 destructive
- Users sign in with
- OAuth
- OAuth app
- Your own LeadBoxer MCP server app
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 LeadBoxer MCP connection
In AgentKit > Connections, create a LeadBoxer MCP connection and copy its redirect URI. The name you give it is the
connection_nameyour code passes. See Configure connections.Register an OAuth app
LeadBoxer MCP server connections use your own OAuth app. Register one with LeadBoxer MCP server and add the redirect URI you copied.
Then enter the app's Client ID and Client Secret on the LeadBoxer MCP connection.
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 = 'leadboxermcp'const identifier = 'user_123'// Generate an authorization link for the userconst { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })console.log('Authorize LeadBoxer 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: 'leadboxermcp_list_specs',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 = "leadboxermcp"identifier = "user_123"# Generate an authorization link for the userlink_response = actions.get_authorization_link(connection_name=connection_name,identifier=identifier,)print("Authorize LeadBoxer MCP:", link_response.link)input("Press Enter after authorizing...")# Make your first callresult = actions.execute_tool(tool_input={},tool_name="leadboxermcp_list_specs",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_toolleadboxermcp_get_endpointGets detailed information about a specific API endpoint, including security schemes and servers.Read-onlyGet Endpoint
Gets detailed information about a specific API endpoint, including security schemes and servers.
Inputs
methodstringrequired- The HTTP method (e.g. GET, POST, PUT, DELETE).
pathstringrequired- The API endpoint path (e.g. /api/v1/users).
titlestringrequired- Title of the OpenAPI spec.
leadboxermcp_list_endpointsLists all API paths and their HTTP methods with summaries, organized by path.Read-onlyList Endpoints
Lists all API paths and their HTTP methods with summaries, organized by path. Results can be passed directly into 'get-endpoint'.
Inputs
titlestringrequired- Title of the OpenAPI spec. Use tool 'list-specs' or 'search-endpoints' to see available specs.
leadboxermcp_list_specsLists all available OpenAPI specs.Read-onlyList Specs
Lists all available OpenAPI specs. Use the title to select a spec.
Inputs
This tool takes no inputs.
leadboxermcp_search_endpointsPerforms a deep search through paths, operations, and parameters to discover relevant API endpoints.Read-onlySearch Endpoints
Performs a deep search through paths, operations, and parameters to discover relevant API endpoints.
Inputs
patternstringrequired- Search pattern (case-insensitive).
leadboxermcp_execute_requestExecutes an API request with a given HAR request object.DestructiveExecute Request
Executes an API request with a given HAR request object.
Inputs
harRequestobjectrequired- HAR request object describing the API call to execute.
titlestringrequired- Title of the OpenAPI spec.
No tools match.