LeadBoxer MCP

Live

OAUTH 2.0

ANALYTICS

Analytics

Connect to LeadBoxer MCP to identify anonymous website visitors and enrich them with firmographic data. LeadBoxer is a B2B lead generation and website...

  • 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.
LeadBoxer MCP
agent · Acme Q3
Run
Execute Request in LeadBoxer MCP
S
leadboxermcp_execute_request
85ms
LeadBoxer MCP agent
Executes an api request with a given har request object..
Sources: LeadBoxer MCP
leadboxermcpmcp
1 tool call
18:29
Message Claude...

LeadBoxer MCP tools for AI agents

CALL ANY TOOL
5 tools covering get, execute, list.
leadboxermcp_execute_request
Executes an api request with a given har request object.
Executes an api request with a given har request object.
Parameters
Name
Type
Required
Description
harRequest
object
Required
HAR request object describing the API call to execute.
title
string
Required
Title of the OpenAPI spec.
leadboxermcp_get_endpoint
Gets detailed information about a specific api endpoint, inc
leadboxermcp_list_endpoints
Lists all api paths and their http methods with summaries, o
leadboxermcp_list_specs
Lists all available openapi specs. use the title to select a
leadboxermcp_search_endpoints
Performs a deep search through paths, operations, and parame
Build your Agent
Same auth pattern across every framework.
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="leadboxermcp")

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

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

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/leadboxermcp
// 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="leadboxermcp")
# Connect to MCP at https://mcp.scalekit.com/leadboxermcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Performs a deep search through paths, operations, and parameters to discover relevant API endpoints?
Copy the prompt
Copied
Lists all available OpenAPI specs?
Advanced
Copy the prompt
Copied
Gets detailed information about a specific API endpoint, including security schemes and servers?
Copy the prompt
Copied
Executes an API request with a given HAR request object?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
LeadBoxer 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
LeadBoxer 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
LeadBoxer 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
LeadBoxer 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.
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 LeadBoxer 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 LeadBoxer 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 LeadBoxer?
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 LeadBoxer.

What happens when a user revokes LeadBoxer 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 LeadBoxer dataset does visitor identification query?
The authorizing user's. Endpoint calls run against that user's LeadBoxer account and datasets, so visitor and firmographic data stays tenant-isolated.

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