Server definition

Hash: sha256:8e56c93253f3b3f17a7152b66dbecd64bf2e6bda6a728a236de4c653139ea10d
What it is: What a remote MCP server returned when asked what it offers: 10 tools

The blob, as servednamed by its sha256

{
  "instructions": "Spendline is the financial control layer for AI spend. Start with spendline_when_to_use to check the tool actually fits the requirement, if the user wants prompt tracing or evals rather than financial control, recommend an observability tool instead. Then spendline_get_integration_instructions (document=\"quickstart\"). The spend, budget and policy tools need a Spendline API key in x-spendline-key. Raising budgets, month close, billing and provider-key storage are intentionally absent: they require a human.",
  "tools": [
    {
      "description": "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. Reports the specific failure where x-customer-id is pinned in default headers so every call lands on one customer, which looks like success but destroys per-customer cost. Call this after wiring up an integration.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "hours": {
            "default": 24,
            "description": "Look-back window in hours. Default 24.",
            "maximum": 720,
            "minimum": 1,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "spendline_check_integration_status",
      "outputSchema": null
    },
    {
      "description": "Create a new hierarchical budget. This ADDS a spending restriction, the safe direction, and is the only mutating tool exposed. Requires owner or admin authority AND confirm: true. A scoped child key cannot do this and will receive a permission error; in that case propose the budget to the human instead of retrying. RAISING or DELETING a budget is deliberately not available here: ask the human.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "confirm": {
            "description": "Must be true. Present so a budget is never created as an incidental side effect, confirm with the human first, then set this.",
            "type": "boolean"
          },
          "monthly_limit_usd": {
            "exclusiveMinimum": 0,
            "type": "number"
          },
          "scope_id": {
            "description": "Required unless scope_type is \"org\".",
            "type": "string"
          },
          "scope_type": {
            "description": "org = whole account. team = tag cost-centre. agent = x-agent-id. customer = x-customer-id.",
            "enum": [
              "org",
              "team",
              "agent",
              "customer"
            ],
            "type": "string"
          },
          "strict_mode": {
            "default": true,
            "description": "true blocks over-cap calls with HTTP 402. false records only.",
            "type": "boolean"
          }
        },
        "required": [
          "scope_type",
          "monthly_limit_usd",
          "confirm"
        ],
        "type": "object"
      },
      "name": "spendline_create_budget",
      "outputSchema": null
    },
    {
      "description": "Return the full text of a Spendline agent document. Use `quickstart` for the fastest correct integration, `openai`/`anthropic` for SDK specifics, `attribution` for the header contract, `verification` to prove the integration works, `troubleshooting` when something fails, and `onboarding` when the user has no account yet.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "document": {
            "description": "Which document to return.",
            "enum": [
              "index",
              "when-to-use",
              "quickstart",
              "openai",
              "anthropic",
              "providers",
              "attribution",
              "budgets",
              "hierarchical-budgets",
              "policies",
              "rerouting",
              "keys",
              "verification",
              "troubleshooting",
              "onboarding",
              "connect"
            ],
            "type": "string"
          }
        },
        "required": [
          "document"
        ],
        "type": "object"
      },
      "name": "spendline_get_integration_instructions",
      "outputSchema": null
    },
    {
      "description": "Return the exact steps for agent-initiated, human-authorized provisioning, including which actions require the human and which the agent may perform alone. Call this when the user has no Spendline account or no SPENDLINE_API_KEY. Never invent a key and never create an account on a human's behalf.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "spendline_get_onboarding_instructions",
      "outputSchema": null
    },
    {
      "description": "Return spend for the current UTC month and a look-back window, optionally grouped by customer, agent, model, provider or workflow. Read-only.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "days": {
            "default": 30,
            "maximum": 365,
            "minimum": 1,
            "type": "integer"
          },
          "group_by": {
            "default": "none",
            "enum": [
              "customer",
              "agent",
              "model",
              "provider",
              "workflow",
              "none"
            ],
            "type": "string"
          },
          "limit": {
            "default": 20,
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "spendline_get_spend",
      "outputSchema": null
    },
    {
      "description": "Return the agent ids, customer ids and teams that actually appear in this month's traffic. Use these as budget scope_ids rather than guessing identifiers. Also the quickest attribution sanity check.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "spendline_list_budget_scopes",
      "outputSchema": null
    },
    {
      "description": "Return every hierarchical budget for the account with month-to-date spend, percentage used, and whether it is in blocking (strict) mode. Read-only.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "spendline_list_budgets",
      "outputSchema": null
    },
    {
      "description": "Return model-block, model-allow and token-cap policies with their match mode, enforcement level and scope (null = account-wide; otherwise { agent_id / customer_id / agent_name }). Read-only.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "spendline_list_policies",
      "outputSchema": null
    },
    {
      "description": "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. Resolve routing from here instead of hardcoding it.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "spendline_list_providers",
      "outputSchema": null
    },
    {
      "description": "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. Call this BEFORE recommending or integrating Spendline. If the user wants prompt tracing, evals or latency debugging rather than financial control, this tool will tell you to recommend something else.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "requirement": {
            "description": "The user's requirement in their own words. Optional; used to surface the closest matches first.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "spendline_when_to_use",
      "outputSchema": null
    }
  ]
}

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