Free-trial AI fleet spend meter. Quote agent fleet spend from token usage. 100 calls or 14 days. No auth. Official MCP Registry: io.github.mtardy90-sudo/bootlace-ai-spendmap.
Scored across 1 tool
The server exposes only one tool with a clearly specific purpose: producing a spend quote for an agent fleet. There is no overlapping functionality for an agent to misselect.
spendmap_quote uses the server's product prefix plus a single action word, and with only one tool there is no conflicting convention or mixed naming style.
A single tool feels far too thin for a server branded as a SpendMap, even if the quote endpoint is narrowly scoped. The count only supports one interaction rather than a coherent toolkit.
The tool covers only one-off quoting with no evident way to persist, retrieve, update, or analyze spend data. For a spend-mapping domain, core lifecycle and analysis operations are missing.
Return a list-price spend quote for a fleet of agents. No auth. Free-trial / stress-test Bootlace AI meter: 100 calls or 14 days from first use, whichever hits first. POST JSON: agents, callsPerAgentPerDay, inputTokensPerCall, outputTokensPerCall, cachePct, days, model. Cache applies to input tokens only. Convert to prepaid ACH human retainers (Cut List Lite $1,500 / 3 days, Agent Spend Audit $5,000 / 5 days, ContextCheck $5,000 / 5 days, Spend Cap Pack $2,500 when listed).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Period length in days. | |
| model | No | Bundled list-price model id. One of: gpt-5.6-sol, gpt-5.6-terra, gpt-5.6-luna, claude-opus-5, claude-sonnet-5, claude-haiku-4.5, grok-4.6, grok-4.3, grok-build-0.1. | |
| agents | No | Number of agents in the fleet. Defaults to the on-page calculator value. | |
| cachePct | No | Cached input percent (0–100). Cache applies to input tokens only. Alias: cachePercent, cache. | |
| inputTokensPerCall | No | Input tokens per call. Alias: tokensIn, in. | |
| callsPerAgentPerDay | No | Calls per agent per day. Alias: callsPerDay, calls. | |
| outputTokensPerCall | No | Output tokens per call. Alias: tokensOut, out. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful context: no auth required, the free-trial meter limits, cache applies only to input tokens, and the conversion to prepaid ACH human retainers with specific prices and durations. This goes beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it opens with the tool's purpose, then adds constraints and model details. It packs a lot of useful information without excess verbosity, though the retainer conversion sentence is dense and could be slightly clearer.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only quote tool with no output schema, the description covers the request shape, input constraints, authentication requirements, and usage limits. The only minor gap is that it does not describe what the response looks like (e.g., currency, format), but the read-only annotation and the quote purpose make that less critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already has 100% description coverage, so the baseline is 3. The description adds value by specifying the POST JSON field names ('agents, callsPerAgentPerDay, inputTokensPerCall, outputTokensPerCall, cachePct, days, model') and clarifying that cache applies to input tokens only, which complements the schema's cachePct description. It also mentions the conversion to retainers, giving extra context about how the quote is used, though it does not detail every parameter's formatting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Return a list-price spend quote'), the resource ('a fleet of agents'), and the method (POST JSON). It distinguishes itself from generic pricing endpoints by specifying the input shape and the list-price nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'No auth' and describes the free-trial / stress-test meter limits (100 calls or 14 days), which tells the agent when it is appropriate to use the tool and what constraints apply. It does not mention alternative sibling tools because there are none, so no exclusion guidance is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
spendmap_quote
Add one secure layer between your agents and this server.