Home / Token cost / Sats4AI - Bitcoin-Powered AI Tools

The Sats4AI - Bitcoin-Powered AI Tools MCP server costs 31,028 tokens before the first call.

Connect Sats4AI - Bitcoin-Powered AI Tools and its 49 tool definitions are loaded into the model's context on every request — 16% of a 200k window spent before your agent does anything.

QUICK ANSWER The Sats4AI - Bitcoin-Powered AI Tools MCP server's tool definitions consume 31,028 tokens — 16× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 49 tools · 31,028 tokens · 16% of 200k · 3.1% 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 16%
1M WINDOW 3.1%

Corpus context: Sats4AI - Bitcoin-Powered AI Tools ranks #24 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 31,028 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 633 tokens per tool.

ToolCategoryTokens% of server
text_to_speech Write 18,176 58.6%
translate_text Read 1,363 4.4%
create_payment Financial 623 2.0%
ai_call Write 541 1.7%
open_voice_bridge Write 489 1.6%
epub_to_audiobook Write 488 1.6%
generate_music Write 437 1.4%
receive_fax Write 354 1.1%
send_fax Write 348 1.1%
check_job_status Read 328 1.1%
generate_text Write 321 1.0%
transcribe_translate Read 306 1.0%
restore_face Write 283 0.9%
voice_bridge_say Write 278 0.9%
edit_image Write 276 0.9%
get_job_result Read 274 0.9%
deblur_image Write 264 0.9%
generate_video Write 259 0.8%
list_models Read 255 0.8%
get_cost_estimate Read 253 0.8%
remove_object Destructive 247 0.8%
convert_file Write 243 0.8%
detect_objects Read 242 0.8%
upscale_image Write 242 0.8%
clone_voice Write 230 0.7%
generate_3d_model Write 230 0.7%
transcribe_audio Write 230 0.7%
request_refund Financial 229 0.7%
place_call Write 218 0.7%
convert_html_to_pdf Write 212 0.7%
animate_image Write 204 0.7%
generate_image Write 204 0.7%
send_email Write 195 0.6%
send_sms Write 187 0.6%
colorize_image Write 185 0.6%
merge_pdfs Write 181 0.6%
analyze_image Read 172 0.6%
extract_receipt Read 169 0.5%
remove_background Destructive 163 0.5%
extract_document Read 161 0.5%
detect_nsfw Read 156 0.5%
confirm_ai_call Write 140 0.5%
vote_on_service Write 137 0.4%
check_payment_status Read 131 0.4%
poll_voice_bridge Read 105 0.3%
list_planned_services Read 88 0.3%
get_error_codes Read 84 0.3%
end_voice_bridge Write 73 0.2%
get_model_pricing Read 54 0.2%

Most agents use a handful of these tools. They pay for all 49.

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 (633 tokens each).

Grant scopeDefinition costReduction
All 49 tools (no gateway) 31,028 tokens
3 granted tools ~1,900 tokens −94%
5 granted tools ~3,166 tokens −90%
10 granted tools ~6,332 tokens −80%

Sats4AI - Bitcoin-Powered AI Tools token-cost questions.

How many tokens does the Sats4AI - Bitcoin-Powered AI Tools MCP server use?+

Its 49 tool definitions total 31,028 tokens — 16% 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 Sats4AI - Bitcoin-Powered AI Tools 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 Sats4AI - Bitcoin-Powered AI Tools's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Sats4AI - Bitcoin-Powered AI Tools 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 1,900 tokens, a 94% 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 49 catalogued Sats4AI - Bitcoin-Powered AI Tools tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Sats4AI - Bitcoin-Powered AI Tools 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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