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The Vocab Voyage MCP server costs 3,831 tokens before the first call.

Connect Vocab Voyage and its 31 tool definitions are loaded into the model's context on every request — 1.9% of a 200k window spent before your agent does anything.

QUICK ANSWER The Vocab Voyage MCP server's tool definitions consume 3,831 tokens — 2.0× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 31 tools · 3,831 tokens · 1.9% of 200k · 0.4% 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 1.9%
1M WINDOW 0.4%

Corpus context: Vocab Voyage ranks #1177 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 3,831 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 124 tokens per tool.

ToolCategoryTokens% of server
play_game Read 287 7.5%
file_support_ticket Read 246 6.4%
nudge_child Read 190 5.0%
generate_quiz Write 177 4.6%
record_word_result Read 176 4.6%
get_session_detail Read 173 4.5%
record_session_complete Write 171 4.5%
get_recent_mistakes Read 165 4.3%
get_flashcards Read 163 4.3%
study_plan_preview Write 155 4.0%
get_word_of_the_day Read 139 3.6%
get_class_standing Read 126 3.3%
get_child_session_detail Read 122 3.2%
get_class_session_trends Read 122 3.2%
get_study_plan_recommendation Read 122 3.2%
resend_pending_invite Write 113 2.9%
get_definition Read 108 2.8%
get_session_trends Read 105 2.7%
get_pending_invites Read 103 2.7%
get_sparkle_guidance Read 101 2.6%
update_adaptive_level Write 98 2.6%
get_my_progress Read 93 2.4%
award_game_xp Execute 87 2.3%
set_persona Write 77 2.0%
get_course_word_list Read 72 1.9%
explain_word_in_context Read 67 1.7%
get_recommended_next_action Read 65 1.7%
mark_word_known Write 62 1.6%
mark_word_difficult Write 59 1.5%
list_starter_prompts Read 52 1.4%
list_courses Read 35 0.9%

Most agents use a handful of these tools. They pay for all 31.

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 (124 tokens each).

Grant scopeDefinition costReduction
All 31 tools (no gateway) 3,831 tokens
3 granted tools ~371 tokens −90%
5 granted tools ~618 tokens −84%
10 granted tools ~1,236 tokens −68%

Vocab Voyage token-cost questions.

How many tokens does the Vocab Voyage MCP server use?+

Its 31 tool definitions total 3,831 tokens — 1.9% 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 Vocab Voyage 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 Vocab Voyage's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Vocab Voyage 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 371 tokens, a 90% 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 31 catalogued Vocab Voyage tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Vocab Voyage 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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