Home / Token cost / MRC Data — China's Apparel Supply Chain Infrastructure

The MRC Data — China's Apparel Supply Chain Infrastructure MCP server costs 16,077 tokens before the first call.

Connect MRC Data — China's Apparel Supply Chain Infrastructure and its 19 tool definitions are loaded into the model's context on every request — 8.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The MRC Data — China's Apparel Supply Chain Infrastructure MCP server's tool definitions consume 16,077 tokens — 8.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 19 tools · 16,077 tokens · 8.0% of 200k · 1.6% 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 8.0%
1M WINDOW 1.6%

Corpus context: MRC Data — China's Apparel Supply Chain Infrastructure ranks #83 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 16,077 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 846 tokens per tool.

ToolCategoryTokens% of server
search_suppliers Read 1,393 8.7%
search_fabrics Read 1,303 8.1%
search_clusters Read 1,033 6.4%
find_alternatives Read 976 6.1%
recommend_suppliers Destructive 933 5.8%
get_supplier_detail Read 930 5.8%
detect_discrepancy Read 927 5.8%
check_compliance Read 877 5.5%
get_fabric_detail Read 825 5.1%
estimate_cost Destructive 820 5.1%
compare_suppliers Execute 770 4.8%
get_cluster_suppliers Read 728 4.5%
get_supplier_fabrics Read 716 4.5%
compare_clusters Execute 714 4.4%
get_fabric_suppliers Read 712 4.4%
analyze_market Read 633 3.9%
get_province_distribution Read 613 3.8%
get_stats Read 608 3.8%
get_product_categories Read 566 3.5%

Most agents use a handful of these tools. They pay for all 19.

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 (846 tokens each).

Grant scopeDefinition costReduction
All 19 tools (no gateway) 16,077 tokens
3 granted tools ~2,538 tokens −84%
5 granted tools ~4,231 tokens −74%
10 granted tools ~8,462 tokens −47%

MRC Data — China's Apparel Supply Chain Infrastructure token-cost questions.

How many tokens does the MRC Data — China's Apparel Supply Chain Infrastructure MCP server use?+

Its 19 tool definitions total 16,077 tokens — 8.0% 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 MRC Data — China's Apparel Supply Chain Infrastructure 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 MRC Data — China's Apparel Supply Chain Infrastructure's token usage?+

Expose fewer tools. A PolicyLayer grant scopes MRC Data — China's Apparel Supply Chain Infrastructure 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 2,538 tokens, a 84% 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 19 catalogued MRC Data — China's Apparel Supply Chain Infrastructure tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes MRC Data — China's Apparel Supply Chain Infrastructure 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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