← boardroom-ai.ae
INDIVIDUAL MCP TOOL
whoami
Who this token is, which workspace it can read, and which scopes it carries.
LIVE ENDPOINT
https://control.boardroom-ai.ae/mcp
Connect to this endpoint to inspect the live schema for whoami and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- A tool name, description or schema mentions credentials.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.boardroom-control-revenue]
url = "https://control.boardroom-ai.ae/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"boardroom-control-revenue": {
"type": "http",
"url": "https://control.boardroom-ai.ae/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: boardroom-control-revenue
Remote MCP URL: https://control.boardroom-ai.ae/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"boardroom-control-revenue": {
"url": "https://control.boardroom-ai.ae/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"boardroom-control-revenue": {
"type": "http",
"url": "https://control.boardroom-ai.ae/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "boardroom-control-revenue",
"transport": "streamable-http",
"url": "https://control.boardroom-ai.ae/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
crm_list_leads— Leads in this workspace, newest activity first.crm_get_lead— One lead in full — unmasked contact details, notes, events, stage history and open tasks.crm_pipeline_overview— Every pipeline and stage with its lead count and total value.crm_leads_without_task— Open leads with no unfinished task against them — the follow-up leak.ad_attribution— Which advertisement produced which conversation: ad id, creative, first-touch flag, and the lead it bound to.agent_conversations— Conversations the AI agent handled, with intent, language, message count and the deal they bound to.agent_get_conversation— One conversation with its transcript — what the customer wrote and what the agent answered.dashboard_snapshot— The workspace's own KPI contract as the dashboard renders it, with the time it was built.