
Spendline MCP server
Which servers in the official MCP registry are Spendline's own, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.
read 2026-10-20
- Registry nameai.spendline/spendlineverified in the MCP registry
The registry name sits under spendline.ai. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.
- Stateanswerschecked 2026-10-20
- Tools10
- Server calls itselfspendline
- Server version1.0.0
- Protocol version2025-06-18
On 2026-10-20 the server answered initialize and tools/list without a sign-in. First answer in 174 ms.
- Whether its tools do the product's job has not been judged yet.
- Checked on 3 of the 7 days it takes to judge reliability.
Once connected
- spendline_create_budget change data without a sign-in: anyone with the address can call them.
Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.
- INITE MCP scoreafter a weeka score needs 7 daily checks: 3 so far
- Answeredmeasuring3 of the 7 daily checks it takes to print a share
- Median first answer244 ms
- Space in an agent's context≈ 1,395 tokensthe definitions of all its tools (10), which an agent carries on every turn
- Tool definitionsA · 97 of 100
- Typed results0 of 10 toolsdeclared outputSchema: results come typed, read once
- Parameters without a description: in 2 of 10
What an agent can do with it
- can do · attribute AI provider spend to each customer and workflow
- not sure · compare each customer's AI cost against what they pay
- not sure · refuse or approve model calls that exceed set budgets
Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?
Worth a look
- Tools that change data, on a server that answers without a sign-in: spendline_create_budget
A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (30%), doing the product's job (25%), definitions (20%), context (10%) and use (15%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →
spendline_when_to_useReturn 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_list_providersReturn 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…
spendline_get_integration_instructionsReturn 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…
spendline_get_onboarding_instructionsReturn 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…
spendline_check_integration_statusVerify 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…
spendline_get_spendReturn spend for the current UTC month and a look-back window, optionally grouped by customer, agent, model, provider or workflow. Read-only.
spendline_list_budgetsReturn every hierarchical budget for the account with month-to-date spend, percentage used, and whether it is in blocking (strict) mode. Read-only.
spendline_list_policiesReturn 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.
spendline_list_budget_scopesReturn 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.
spendline_create_budgetCreate 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…
How to connect
Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:
{
"mcpServers": {
"spendline": {
"type": "http",
"url": "https://www.spendline.ai/mcp"
}
}
}Add it
Claude Code, in a terminal
claude mcp add --transport http spendline https://www.spendline.ai/mcpclaude.ai, ChatGPT and other clients: add https://www.spendline.ai/mcp as a custom connector in the settings.
OpenAPI spec
20 paths, read 2026-10-20. Open the spec ↗
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
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