LogRocket MCP connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. 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>

3. Authorize and make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'logrocketmcp'
   const identifier = 'user_123'
   
   // Generate an authorization link for the user
   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
   console.log('Authorize LogRocket MCP:', link)
   process.stdout.write('Press Enter after authorizing...')
   await new Promise(r => process.stdin.once('data', r))
   
   // Make your first call
   const result = await actions.executeTool({
     connector,
     identifier,
     toolName: 'logrocketmcp_list_organizations',
     toolInput: {},
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "logrocketmcp"
   identifier = "user_123"
   
   # Generate an authorization link for the user
   link_response = actions.get_authorization_link(
       connection_name=connection_name,
       identifier=identifier,
   )
   print("Authorize LogRocket MCP:", link_response.link)
   input("Press Enter after authorizing...")
   
   # Make your first call
   result = actions.execute_tool(
       tool_input={},
       tool_name="logrocketmcp_list_organizations",
       connection_name=connection_name,
       identifier=identifier,
   )
   print(result)

What you can do

Connect this agent connector to let your agent:

• Logrocket use — Process a natural language query against LogRocket data — sessions, metrics, and issues
• List projects, organizations — List all projects within a LogRocket organization

Tool list

Use the exact tool names from the Tool list below when you call execute_tool. If you’re not sure which name to use, list the tools available for the current user first.

logrocketmcp_list_organizations#List all LogRocket organizations the authenticated user has access to. Use this first to discover available organizations before querying projects or sessions.0 params▾

List all LogRocket organizations the authenticated user has access to. Use this first to discover available organizations before querying projects or sessions.

logrocketmcp_list_projects#List all projects within a LogRocket organization. Use this to identify accessible projects before querying sessions, metrics, or issues.1 param▾

List all projects within a LogRocket organization. Use this to identify accessible projects before querying sessions, metrics, or issues.

NameTypeRequiredDescription

organizationSlugstringrequiredThe slug of the LogRocket organization. Use the list_organizations tool to find available organization slugs.

logrocketmcp_use_logrocket#Process a natural language query against LogRocket data — sessions, metrics, and issues. Use this to investigate user-reported bugs, understand behavior patterns, analyze performance metrics, and detect regressions by correlating code changes with LogRocket data.3 params▾

Process a natural language query against LogRocket data — sessions, metrics, and issues. Use this to investigate user-reported bugs, understand behavior patterns, analyze performance metrics, and detect regressions by correlating code changes with LogRocket data.

NameTypeRequiredDescription

organizationSlugstringrequiredThe slug of the LogRocket organization to query. Use the list_organizations tool to find available slugs.

projectSlugstringrequiredThe slug of the LogRocket project to query. Use the list_projects tool to find available slugs.

querystringrequiredNatural language query describing what to investigate. Examples: 'show me sessions where users encountered a checkout error', 'how many users hit the payment failure last week', 'find sessions with rage clicks on the signup button'.