LogRocket MCP

Live

OAUTH 2.0

ANALYTICS

Analytics

Connect to LogRocket to access session data, query analytics, investigate user-reported issues, and detect regressions directly from your AI workflows.

  • 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.
LogRocket MCP
agent · Acme Q3
Run
List Organizations in LogRocket MCP
S
logrocketmcp_list_organizations
85ms
LogRocket MCP agent
List all logrocket organizations the authenticated user has access to. use this first to discover available organization.
Sources: LogRocket MCP
logrocketmcpmcp
1 tool call
18:29
Message Claude...

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

CALL ANY TOOL
Query sessions, investigate reported issues, and detect regressions across the user's projects.
logrocketmcp_list_organizations
List all logrocket organizations the authenticated user has
List all logrocket organizations the authenticated user has access to. use this first to discover available organizations before querying projects or sessions.
Parameters
Name
Type
Required
Description
No parameters required
logrocketmcp_list_projects
List all projects within a logrocket organization. use this
logrocketmcp_use_logrocket
Process a natural language query against logrocket data — se
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="logrocketmcp")

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

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

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/logrocketmcp
// 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="logrocketmcp")
# Connect to MCP at https://mcp.scalekit.com/logrocketmcp
# Pass: Authorization: Bearer + token
Try these prompts
Copy any prompt into your agent. Each maps directly to a LogRocket tool. Click to copy, paste into your agent, done.
Get started
Copy the prompt
Copied
Process a natural language query against LogRocket data — sessions, metrics, and issues?
Copy the prompt
Copied
List all projects within a LogRocket organization?
Advanced
Copy the prompt
Copied
Process a natural language query against LogRocket data — sessions, metrics, and issues?
Copy the prompt
Copied
List all projects within a LogRocket organization?
SEE HOW AUTH WORKS
Your users connect once. Their LogRocket credentials stay vaulted, every call is scope-checked, and every action is logged.
1
Authorize
Your user connects
LogRocket 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
LogRocket 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
LogRocket 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
LogRocket 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.
SALES
Deal intelligence agent
Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.
ENGINEERING
Engineering standup agent
Aggregate GitHub and GitLab activity, link to Jira, and post a daily standup digest to Slack. No async updates.
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 LogRocket 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 LogRocket 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 LogRocket?
Yes. Pass a tool name filter to listScopedTools so the analytics agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches LogRocket.

What happens when a user revokes LogRocket 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.

Which session recordings can the agent investigate?
Only projects the authorizing user can access in LogRocket. Session queries and regression checks follow organization membership, keeping user session data inside the right team.

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"": {
""logrocketmcp"": {
""url"": ""https://mcp.scalekit.com/logrocketmcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.logrocketmcp]
url = ""https://mcp.scalekit.com/logrocketmcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""logrocketmcp"": {
""url"": ""https://mcp.scalekit.com/logrocketmcp"",
""type"": ""http""
}
}
}