INDIVIDUAL MCP TOOL

spendline_get_onboarding_instructions

Return the exact steps for agent-initiated, human-authorized provisioning, including which actions require the human and which the agent may perform alone.

spendline.ainone authenticationAvailability not checked

LIVE ENDPOINT

https://www.spendline.ai/mcp

No auth detected

Connect to this endpoint to inspect the live schema for spendline_get_onboarding_instructions and invoke it with your own arguments.

Indexed input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

Parent server

spendline.ai

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.spendline]
url = "https://www.spendline.ai/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "spendline": {
      "type": "http",
      "url": "https://www.spendline.ai/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: spendline
Remote MCP URL: https://www.spendline.ai/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": {
    "spendline": {
      "url": "https://www.spendline.ai/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "spendline": {
      "type": "http",
      "url": "https://www.spendline.ai/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "spendline",
  "transport": "streamable-http",
  "url": "https://www.spendline.ai/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

Related tools

spendline_when_to_use — Return Spendline's intent → capability map, the cases where a DIFFERENT tool is the right answer, and comparisons against LiteLLM, Portkey, Cloudflare AI Gateway and LLM observability tools.
spendline_list_providers — Return every provider Spendline can proxy, the three accepted request shapes, the exact base URL to set per SDK (including the OpenAI-vs-Anthropic /v1 asymmetry), the required attribution headers, and the request shapes that are NOT proxied.
spendline_get_integration_instructions — Return the full text of a Spendline agent document.
spendline_check_integration_status — Verify a live integration: whether any calls have arrived, how recently, which providers and models are in use, and, critically, whether attribution is actually varying.
spendline_get_spend — Return spend for the current UTC month and a look-back window, optionally grouped by customer, agent, model, provider or workflow.
spendline_list_budgets — Return every hierarchical budget for the account with month-to-date spend, percentage used, and whether it is in blocking (strict) mode.
spendline_list_policies — Return model-block and token-cap policies with their match mode and enforcement level.
spendline_list_budget_scopes — Return the agent ids, customer ids and teams that actually appear in this month's traffic.