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The Weatherdemo MCP server costs 16,733 tokens before the first call.

Connect Weatherdemo and its 59 tool definitions are loaded into the model's context on every request — 8.4% of a 200k window spent before your agent does anything.

QUICK ANSWER The Weatherdemo MCP server's tool definitions consume 16,733 tokens — 8.8× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 59 tools · 16,733 tokens · 8.4% of 200k · 1.7% of 1M Method →

What that buys 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 8.4%
1M WINDOW 1.7%

Corpus context: Weatherdemo ranks #69 of 3,213 measured MCP servers by definition cost. The median is 1,905 tokens, p90 is 7,952, and the heaviest (Fusionauth) is 183,337 — 92% of a 200k window on its own.

Where the 16,733 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 284 tokens per tool.

ToolCategoryTokens% of server
alerts_query Read 1,612 9.6%
alerts_active Read 1,212 7.2%
radar_queue Read 1,168 7.0%
zone_list_type Read 1,102 6.6%
zone_list Read 1,049 6.3%
gridpoint_forecast_hourly Read 644 3.8%
gridpoint_forecast Read 641 3.8%
gridpoint_stations Read 618 3.7%
obs_stations Read 580 3.5%
products_query Read 528 3.2%
gridpoint Read 506 3.0%
radar_profiler Read 485 2.9%
station_observation_list Read 456 2.7%
alerts_active_area Read 455 2.7%
sigmetQuery Read 450 2.7%
zone_obs Read 448 2.7%
cwa Read 312 1.9%
zone Read 283 1.7%
sigmet Read 265 1.6%
taf Read 265 1.6%
station_observation_time Read 235 1.4%
sigmetsByATSUByDate Read 221 1.3%
zone_stations Read 187 1.1%
iconsDualCondition Read 172 1.0%
icons Read 158 0.9%
cwas Read 139 0.8%
office_headline Read 137 0.8%
cwsu Read 135 0.8%
radar_stations Read 128 0.8%
obs_station Read 127 0.8%
office_headlines Read 121 0.7%
radar_station Read 118 0.7%
office Read 115 0.7%
radar_server Read 93 0.6%
station_observation_latest Read 93 0.6%
point_radio Read 91 0.5%
point_stations Read 91 0.5%
point Read 88 0.5%
latest_product_type_location Write 83 0.5%
zone_forecast Read 81 0.5%
products_type_location Write 81 0.5%
satellite_thumbnails Read 79 0.5%
alerts_active_region Read 71 0.4%
alerts_active_zone Read 70 0.4%
sigmetsByATSU Read 69 0.4%
products_type_locations Write 66 0.4%
radar_station_alarms Read 65 0.4%
tafs Read 65 0.4%
location_products Read 64 0.4%
radar_servers Read 61 0.4%
products_type Write 61 0.4%
product Read 55 0.3%
alerts_single Read 54 0.3%
icons_summary Read 37 0.2%
product_types Read 31 0.2%
alerts_active_count Read 30 0.2%
product_locations Read 30 0.2%
alerts_types Read 27 0.2%
glossary Read 25 0.1%

Most agents use a handful of these tools. They pay for all 59.

A PolicyLayer grant exposes only the tools you allow — ungranted definitions are filtered out of the tool list, so they never enter the context window. Estimates below assume typical-weight tools (284 tokens each).

Grant scopeDefinition costReduction
All 59 tools (no gateway) 16,733 tokens
3 granted tools ~851 tokens −95%
5 granted tools ~1,418 tokens −92%
10 granted tools ~2,836 tokens −83%

Weatherdemo token-cost questions.

How many tokens does the Weatherdemo MCP server use?+

Its 59 tool definitions total 16,733 tokens — 8.4% 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 Weatherdemo 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 Weatherdemo's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Weatherdemo 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 851 tokens, a 95% 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 07-06-2026 from the PolicyLayer scan database over all 59 catalogued Weatherdemo tools. Counts refresh with every site build.

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

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

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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