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The Options Analytics MCP server costs 4,143 tokens before the first call.

Connect Options Analytics and its 38 tool definitions are loaded into the model's context on every request — 2.1% of a 200k window spent before your agent does anything.

QUICK ANSWER The Options Analytics MCP server's tool definitions consume 4,143 tokens — 2.2× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 38 tools · 4,143 tokens · 2.1% of 200k · 0.4% 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 2.1%
1M WINDOW 0.4%

Corpus context: Options Analytics ranks #1127 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 4,143 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 109 tokens per tool.

ToolCategoryTokens% of server
get_historical_option_quote Read 189 4.6%
calculate_kelly Read 177 4.3%
get_option_quote Read 156 3.8%
calculate_greeks Read 152 3.7%
get_historical_vrp Read 139 3.4%
get_historical_advanced_volatility Read 135 3.3%
get_historical_gex Read 132 3.2%
solve_iv Read 123 3.0%
get_gex Read 121 2.9%
get_historical_exposure_summary Read 120 2.9%
get_historical_zero_dte Read 120 2.9%
get_vrp_history Read 120 2.9%
get_zero_dte Read 118 2.8%
get_historical_levels Read 117 2.8%
get_historical_coverage Read 114 2.8%
get_historical_stock_summary Read 114 2.8%
get_historical_volatility Read 114 2.8%
get_historical_narrative Read 112 2.7%
get_historical_surface Read 110 2.7%
get_historical_max_pain Read 108 2.6%
get_stock_summary Read 105 2.5%
get_historical_vex Read 104 2.5%
get_historical_chex Read 103 2.5%
get_historical_dex Read 102 2.5%
get_historical_stock_quote Read 100 2.4%
get_chex Read 99 2.4%
get_volatility Read 99 2.4%
get_advanced_volatility Read 94 2.3%
get_dex Read 92 2.2%
get_vex Read 92 2.2%
get_exposure_summary Read 86 2.1%
get_vrp Read 82 2.0%
get_levels Read 81 2.0%
get_stock_quote Read 79 1.9%
get_narrative Read 75 1.8%
get_option_chain Read 62 1.5%
get_account Read 50 1.2%
get_tickers Read 47 1.1%

Most agents use a handful of these tools. They pay for all 38.

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 (109 tokens each).

Grant scopeDefinition costReduction
All 38 tools (no gateway) 4,143 tokens
3 granted tools ~327 tokens −92%
5 granted tools ~545 tokens −87%
10 granted tools ~1,090 tokens −74%

Options Analytics token-cost questions.

How many tokens does the Options Analytics MCP server use?+

Its 38 tool definitions total 4,143 tokens — 2.1% 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 Options Analytics 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 Options Analytics's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Options Analytics 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 327 tokens, a 92% 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 38 catalogued Options Analytics tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Options Analytics 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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