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The The Stall MCP server costs 22,904 tokens before the first call.

Connect The Stall and its 105 tool definitions are loaded into the model's context on every request — 11% of a 200k window spent before your agent does anything.

QUICK ANSWER The The Stall MCP server's tool definitions consume 22,904 tokens — 12× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 105 tools · 22,904 tokens · 11% of 200k · 2.3% 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 11%
1M WINDOW 2.3%

Corpus context: The Stall ranks #48 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 22,904 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 218 tokens per tool.

ToolCategoryTokens% of server
yield-farming-active Read 422 1.8%
meme-generator Read 394 1.7%
defi-market-pulse Read 376 1.6%
world-bank-data Read 339 1.5%
generate-meme Write 330 1.4%
dex-trending-pools Read 324 1.4%
defi-yields Read 310 1.4%
funding-rates Read 309 1.3%
research-paper-search Read 303 1.3%
whale-radar Read 296 1.3%
gov-votes Read 291 1.3%
legal-search Read 287 1.3%
sec-filing-intel Read 285 1.2%
market-intelligence Read 281 1.2%
evm-token-security Read 276 1.2%
btc-game-theory Read 272 1.2%
ai-image-gen Read 270 1.2%
limitless-markets Read 266 1.2%
stablecoin-watch Read 266 1.2%
dex-pair-search Read 265 1.2%
nft-metadata Read 265 1.2%
timezone Read 265 1.2%
tx-intel Read 262 1.1%
crypto-fiat-price Read 260 1.1%
clinical-trials Read 259 1.1%
chromatic-dispersion Read 256 1.1%
document-qa-prep Read 254 1.1%
weather Read 252 1.1%
forex-rates Read 251 1.1%
korean-market-movers Read 251 1.1%
web-scrape-links Read 248 1.1%
commodity-futures Read 246 1.1%
wallet-screener Read 243 1.1%
github-repo-intel Read 240 1.0%
polymarket-sentiment-shift Read 240 1.0%
portfolio-rebalance Read 238 1.0%
reddit-intel Read 238 1.0%
regex-tester Read 238 1.0%
classic-novels Read 237 1.0%
market-sentiment Read 234 1.0%
country-info Read 233 1.0%
flight-tracker Read 229 1.0%
erc20-snapshot Read 226 1.0%
fact-check Read 225 1.0%
hn-search Read 223 1.0%
db-perf-intel Read 221 1.0%
market-movers Read 220 1.0%
geocode Read 219 1.0%
equity-technicals Read 218 1.0%
research-synthesis Read 217 0.9%
sports-prediction Read 217 0.9%
crypto-pulse Read 210 0.9%
code-test-detector Read 209 0.9%
company-intel Read 209 0.9%
ssl-cert Read 204 0.9%
npm-lookup Read 200 0.9%
news-sentiment Read 199 0.9%
pypi-lookup Read 199 0.9%
place-details Read 198 0.9%
prediction-markets Read 198 0.9%
strategy-signal Read 198 0.9%
ip-intel Read 197 0.9%
btc-systems-theory Read 196 0.9%
policy-impact-mapper Read 196 0.9%
eth-block Read 194 0.8%
stock-brief Read 193 0.8%
unit-converter Read 193 0.8%
block-intel Read 189 0.8%
tx-explainer Read 187 0.8%
code-api-surface Read 185 0.8%
dns-lookup Read 185 0.8%
btc-miner-econ Read 183 0.8%
citation-formatter Read 183 0.8%
crypto-news-impact Read 183 0.8%
stock-price-multi Read 183 0.8%
http-headers Read 182 0.8%
json-extract Read 182 0.8%
readable-content Read 182 0.8%
sports-scores Read 179 0.8%
earnings-calendar Read 176 0.8%
solana-token-risk Read 175 0.8%
defi-portfolio Read 174 0.8%
image-detect Read 171 0.7%
agent-access-check Read 170 0.7%
city-lookup Read 170 0.7%
company-due-diligence Read 170 0.7%
gas-prices Read 170 0.7%
breadcrumb-extractor Read 167 0.7%
rss-reader Read 164 0.7%
concentration-risk-score Read 163 0.7%
page-intel Read 163 0.7%
wallet-credit-score Read 161 0.7%
crypto-top-movers Read 155 0.7%
roast Read 152 0.7%
us-stock-price Read 150 0.7%
web-company-intel Read 148 0.6%
email-verify Read 147 0.6%
domain-whois Read 145 0.6%
evm-nonce Read 144 0.6%
web-change-monitor Read 142 0.6%
market-overview Read 140 0.6%
gas-estimate Read 119 0.5%
macro-indicators Read 109 0.5%
base-season Read 96 0.4%
ping Read 80 0.3%

Most agents use a handful of these tools. They pay for all 105.

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 (218 tokens each).

Grant scopeDefinition costReduction
All 105 tools (no gateway) 22,904 tokens
3 granted tools ~654 tokens −97%
5 granted tools ~1,091 tokens −95%
10 granted tools ~2,181 tokens −90%

The Stall token-cost questions.

How many tokens does the The Stall MCP server use?+

Its 105 tool definitions total 22,904 tokens — 11% 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 The Stall 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 The Stall's token usage?+

Expose fewer tools. A PolicyLayer grant scopes The Stall 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 654 tokens, a 97% 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 105 catalogued The Stall tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes The Stall 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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