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The Valet Parking Directory MCP server costs 1,632 tokens before the first call.

Every request your agent makes carries every tool definition this server exposes — context your code, documents and conversation can't use, mostly for tools the agent never calls. You don't need them all in the window, and you don't have to pay for them.

QUICK ANSWER The Valet Parking Directory MCP server's 7 tool definitions consume 1,632 tokens — 0.8% of a 200k context window, and around the median MCP server (1,879 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS tiktoken o200k_base · rank #5014 of 9,299 measured servers · refreshed every build Method →

What that costs before your agent starts working.

Tool definitions are overhead: they occupy context on every request and compete with your code, documents and conversation history for the same window.

200K WINDOW 0.8%
1M WINDOW 0.2%

Corpus context: Valet Parking Directory ranks #5014 of 9,299 measured MCP servers by definition cost. The median is 1,879 tokens, p90 is 13,073, and the heaviest (Ainumbers Mcp Apps) is 342,008 — 171% of a 200k window on its own. New to this? See MCP token cost and context window in the glossary.

Where the 1,632 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 233 tokens per tool.

ToolCategoryTokens% of server
valet_find_operators_near Read 363 22.2%
valet_find_nearest_operators Read 293 18.0%
valet_find_operators_in_city Read 290 17.8%
valet_search_by_service_and_city Read 260 15.9%
valet_search_cities Read 175 10.7%
valet_get_operator Read 152 9.3%
valet_list_services Read 99 6.1%

Your agent uses a handful of these tools. It pays for all 7.

You don't need all 7 of those definitions in the window. PolicyLayer is an MCP gateway that sits in front of Valet Parking Directory: only the tools you grant are exposed to the agent, the rest never load. A smaller window means a sharper agent — less noise when it picks a tool — and every request costs less:

Grant scopeDefinition costReduction
All 7 tools (no gateway) 1,632 tokens
3 granted tools ~699 tokens −57%
5 granted tools ~1,166 tokens −29%
  1. Create a free account and register Valet Parking Directory — nothing to install.
  2. Grant only the tools you use — ungranted definitions never enter the context window.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
CUT VALET PARKING DIRECTORY TOKEN COST →

Instant setup, no code required.

Valet Parking Directory token-cost questions.

How many tokens does the Valet Parking Directory MCP server use?+

Its 7 tool definitions total 1,632 tokens — 0.8% of a 200k context window — measured with tiktoken o200k_base over the serialised tools/list payload. Exact counts vary slightly by client and model.

Why does Valet Parking Directory consume tokens before I send a message?+

MCP clients load every connected server's tool definitions — name, description, and input schema — into the model's context so it knows what it can call. That payload is charged against your context window on every request, whether or not a tool is used.

How do I reduce Valet Parking Directory's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Valet Parking Directory to only the tools you allow — ungranted definitions are filtered out of the tool list, so they never enter the context window. A grant of 3 typical tools costs roughly 699 tokens, a 57% reduction.

Does deferred tool loading fix this?+

Partially, in some clients. Claude Code defers MCP tool schemas behind a tool-search step by default, and VS Code has experimental grouping — but you still pay tokens per search and reload, and Cursor, Windsurf and Gemini CLI load definitions upfront. Reducing the exposed tool set cuts the cost in every client.

How these numbers were measured.

01
Serialisation

Each tool is serialised as a tools/list entry — name, description, input schema — from the schemas in the PolicyLayer scan database. Clients differ slightly in framing, so treat counts as close estimates.

02
Tokeniser

tiktoken o200k_base (GPT-4o/o-series). Anthropic's current tokeniser isn't published, so Claude's exact counts will differ; for English text and JSON schemas the totals are close enough to treat these as estimates.

03
Deferred loading

Some clients now defer schema loading (Claude Code's tool search; VS Code experimental grouping). You still pay per search and reload — and Cursor, Windsurf and Gemini CLI load everything upfront.

Computed 20-09-2026 from the PolicyLayer scan database over all 7 catalogued Valet Parking Directory tools. Counts refresh with every site build.

Expose only the tools you use — the rest never enter your context.

A PolicyLayer grant scopes Valet Parking Directory to the tools you actually allow. Ungranted definitions never load, and every call that does run is checked against policy first.

Instant setup, no code required.

46,500+ MCP servers and 515,000+ tools scanned and risk-classified.

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