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The SlideMaster MCP server costs 4,750 tokens before the first call.

Connect SlideMaster and its 32 tool definitions are loaded into the model's context on every request — 2.4% of a 200k window spent before your agent does anything.

QUICK ANSWER The SlideMaster MCP server's tool definitions consume 4,750 tokens — 2.5× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 32 tools · 4,750 tokens · 2.4% of 200k · 0.5% 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 2.4%
1M WINDOW 0.5%

Corpus context: SlideMaster ranks #1056 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 4,750 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 148 tokens per tool.

ToolCategoryTokens% of server
render_slides Write 441 9.3%
topic_to_video Write 331 7.0%
generate_tts Write 330 6.9%
estimate_cost Write 236 5.0%
save_preferences Write 217 4.6%
update_project Write 206 4.3%
youtube_to_outline Write 202 4.3%
generate_video Write 197 4.1%
generate_outline Write 184 3.9%
check_status Read 182 3.8%
analyze_style_image Read 165 3.5%
get_credit_balance Read 157 3.3%
batch_generate_scripts Write 152 3.2%
list_voices Read 126 2.7%
create_project Write 126 2.7%
generate_script Write 122 2.6%
export_pdf Write 114 2.4%
export_pptx Write 106 2.2%
get_credit_transactions Read 102 2.1%
upload_init Write 101 2.1%
get_project_context Read 99 2.1%
update_slide Write 93 2.0%
export_evercam Write 91 1.9%
list_projects Read 84 1.8%
evercam_status Read 81 1.7%
delete_project Destructive 77 1.6%
upload_complete Write 76 1.6%
list_slides Read 75 1.6%
get_preferences Read 74 1.6%
export_project Write 72 1.5%
get_project Read 66 1.4%
delete_slide Destructive 65 1.4%

Most agents use a handful of these tools. They pay for all 32.

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 (148 tokens each).

Grant scopeDefinition costReduction
All 32 tools (no gateway) 4,750 tokens
3 granted tools ~445 tokens −91%
5 granted tools ~742 tokens −84%
10 granted tools ~1,484 tokens −69%

SlideMaster token-cost questions.

How many tokens does the SlideMaster MCP server use?+

Its 32 tool definitions total 4,750 tokens — 2.4% 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 SlideMaster 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 SlideMaster's token usage?+

Expose fewer tools. A PolicyLayer grant scopes SlideMaster 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 445 tokens, a 91% 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 32 catalogued SlideMaster tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes SlideMaster 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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