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The Medical Terminologies MCP server costs 6,491 tokens before the first call.

Connect Medical Terminologies and its 31 tool definitions are loaded into the model's context on every request — 3.2% of a 200k window spent before your agent does anything.

QUICK ANSWER The Medical Terminologies MCP server's tool definitions consume 6,491 tokens — 3.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 31 tools · 6,491 tokens · 3.2% of 200k · 0.6% 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 3.2%
1M WINDOW 0.6%

Corpus context: Medical Terminologies ranks #934 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 6,491 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 209 tokens per tool.

ToolCategoryTokens% of server
validate_codes Read 594 9.2%
terminology_diff Read 419 6.5%
map_icd10_to_icd11 Read 333 5.1%
cid10_search Read 322 5.0%
find_equivalent Read 315 4.9%
atc_lookup Read 287 4.4%
map_loinc_to_snomed Read 275 4.2%
terminology_versions Execute 244 3.8%
mesh_search Read 230 3.5%
atc_members Execute 225 3.5%
icd11_search Read 208 3.2%
cid10_lookup Read 199 3.1%
atc_classify Read 191 2.9%
icd11_lookup Read 190 2.9%
loinc_search Read 178 2.7%
mesh_descriptor Read 174 2.7%
rxnorm_ndc Read 164 2.5%
rxnorm_concept Read 159 2.4%
cid10_chapter Execute 156 2.4%
cid10_chapters Execute 154 2.4%
icd11_hierarchy Read 153 2.4%
loinc_details Execute 150 2.3%
rxnorm_search Read 148 2.3%
mesh_tree Read 141 2.2%
loinc_panels Read 138 2.1%
mesh_qualifiers Execute 134 2.1%
icd11_chapters Read 132 2.0%
loinc_answers Read 132 2.0%
icd11_postcoordination Read 117 1.8%
rxnorm_classes Read 117 1.8%
rxnorm_ingredients Read 112 1.7%

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 (209 tokens each).

Grant scopeDefinition costReduction
All 31 tools (no gateway) 6,491 tokens
3 granted tools ~628 tokens −90%
5 granted tools ~1,047 tokens −84%
10 granted tools ~2,094 tokens −68%

Medical Terminologies token-cost questions.

How many tokens does the Medical Terminologies MCP server use?+

Its 31 tool definitions total 6,491 tokens — 3.2% 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 Medical Terminologies 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 Medical Terminologies's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Medical Terminologies 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 628 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 Medical Terminologies tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Medical Terminologies 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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