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The AI Skill Store MCP server costs 4,600 tokens before the first call.

Connect AI Skill Store and its 18 tool definitions are loaded into the model's context on every request — 2.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The AI Skill Store MCP server's tool definitions consume 4,600 tokens — 2.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 18 tools · 4,600 tokens · 2.3% 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 2.3%
1M WINDOW 0.5%

Corpus context: AI Skill Store ranks #1072 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 4,600 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 256 tokens per tool.

ToolCategoryTokens% of server
upload_skill_draft Write 912 19.8%
upload_skill Write 582 12.7%
search_skills Read 389 8.5%
get_vetting_result Read 372 8.1%
validate_compatibility Read 279 6.1%
get_most_wanted Read 240 5.2%
post_review Write 232 5.0%
download_skill Read 224 4.9%
check_draft_status Read 181 3.9%
register_developer Write 177 3.8%
check_vetting_status Read 168 3.7%
get_install_guide Read 163 3.5%
get_agent_identity_stats Read 154 3.3%
get_agent_author_stats Read 136 3.0%
get_skill_schema Read 134 2.9%
get_skill Read 116 2.5%
list_platforms Read 75 1.6%
list_categories Read 66 1.4%

Most agents use a handful of these tools. They pay for all 18.

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 (256 tokens each).

Grant scopeDefinition costReduction
All 18 tools (no gateway) 4,600 tokens
3 granted tools ~767 tokens −83%
5 granted tools ~1,278 tokens −72%
10 granted tools ~2,556 tokens −44%

AI Skill Store token-cost questions.

How many tokens does the AI Skill Store MCP server use?+

Its 18 tool definitions total 4,600 tokens — 2.3% 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 AI Skill Store 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 AI Skill Store's token usage?+

Expose fewer tools. A PolicyLayer grant scopes AI Skill Store 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 767 tokens, a 83% 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 18 catalogued AI Skill Store tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes AI Skill Store 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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