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The Hormonaly Clinical Intelligence MCP server costs 2,714 tokens before the first call.

Connect Hormonaly Clinical Intelligence and its 24 tool definitions are loaded into the model's context on every request — 1.4% of a 200k window spent before your agent does anything.

QUICK ANSWER The Hormonaly Clinical Intelligence MCP server's tool definitions consume 2,714 tokens — around the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 24 tools · 2,714 tokens · 1.4% of 200k · 0.3% 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 1.4%
1M WINDOW 0.3%

Corpus context: Hormonaly Clinical Intelligence ranks #1361 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 2,714 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 113 tokens per tool.

ToolCategoryTokens% of server
helix_query Read 257 9.5%
run_clinical_workflow Execute 232 8.5%
helix_compare Read 202 7.4%
helix_deep_analysis Execute 195 7.2%
helix_protocol Read 138 5.1%
protocol_search Read 132 4.9%
helix_dossier_start Execute 131 4.8%
monitor_protocol_updates Read 131 4.8%
admin_list_users Read 122 4.5%
evidence_grade Write 120 4.4%
helix_dossier_status Read 106 3.9%
compound_get_dosing Read 105 3.9%
protocol_get_interactions Read 95 3.5%
admin_get_ai_costs Read 88 3.2%
protocol_get Read 87 3.2%
evidence_search Read 86 3.2%
compound_search Read 76 2.8%
admin_get_stats Read 69 2.5%
user_get_profile Read 66 2.4%
user_get_usage Read 66 2.4%
compound_get_interactions Read 61 2.2%
user_get_saved_protocols Read 61 2.2%
evidence_get Read 48 1.8%
protocol_list_categories Read 40 1.5%

Most agents use a handful of these tools. They pay for all 24.

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 (113 tokens each).

Grant scopeDefinition costReduction
All 24 tools (no gateway) 2,714 tokens
3 granted tools ~339 tokens −88%
5 granted tools ~565 tokens −79%
10 granted tools ~1,131 tokens −58%

Hormonaly Clinical Intelligence token-cost questions.

How many tokens does the Hormonaly Clinical Intelligence MCP server use?+

Its 24 tool definitions total 2,714 tokens — 1.4% 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 Hormonaly Clinical Intelligence 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 Hormonaly Clinical Intelligence's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Hormonaly Clinical Intelligence 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 339 tokens, a 88% 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 24 catalogued Hormonaly Clinical Intelligence tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Hormonaly Clinical Intelligence 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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