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The Toofi Dental Planning MCP server costs 7,457 tokens before the first call.

Connect Toofi Dental Planning and its 32 tool definitions are loaded into the model's context on every request — 3.7% of a 200k window spent before your agent does anything.

QUICK ANSWER The Toofi Dental Planning MCP MCP server's tool definitions consume 7,457 tokens — 3.9× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 32 tools · 7,457 tokens · 3.7% of 200k · 0.7% 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 3.7%
1M WINDOW 0.7%

Corpus context: Toofi Dental Planning ranks #740 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 7,457 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 233 tokens per tool.

ToolCategoryTokens% of server
generate_dental_treatment_plan_pdf Write 847 11.4%
get_dental_plan_operation_status Read 596 8.0%
generate_treatment_plan_draft Write 368 4.9%
create_agent_checkout_session Write 299 4.0%
lookup_dental_procedures Read 255 3.4%
get_agent_credit_balance Read 250 3.4%
get_example_result Read 237 3.2%
get_agent_billing_quote Read 223 3.0%
claim_agent_checkout_key Write 221 3.0%
generate_patient_presentation Write 217 2.9%
start_pano_markup Execute 211 2.8%
generate_price_estimate Write 207 2.8%
list_audit_receipts Read 205 2.7%
get_patient Read 200 2.7%
get_plan Read 200 2.7%
list_patients Read 200 2.7%
list_plans Read 200 2.7%
get_status Read 195 2.6%
import_price_csv Write 195 2.6%
get_demo_plan Read 182 2.4%
get_demo_presentation Read 182 2.4%
preview_plan_draft_schema Write 178 2.4%
get_demo_patient Read 175 2.3%
example_ru Read 166 2.2%
example_en Read 165 2.2%
example_ua Read 160 2.1%
discover_capabilities Read 159 2.1%
list_demo_patients Read 159 2.1%
list_demo_plans Read 153 2.1%
example_sk Read 151 2.0%
example_uk Read 151 2.0%
example_pl Read 150 2.0%

Most agents use a handful of these tools. They pay for all 32.

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 (233 tokens each).

Grant scopeDefinition costReduction
All 32 tools (no gateway) 7,457 tokens
3 granted tools ~699 tokens −91%
5 granted tools ~1,165 tokens −84%
10 granted tools ~2,330 tokens −69%

Toofi Dental Planning MCP token-cost questions.

How many tokens does the Toofi Dental Planning MCP server use?+

Its 32 tool definitions total 7,457 tokens — 3.7% 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 Toofi Dental Planning MCP 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 Toofi Dental Planning MCP's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Toofi Dental Planning MCP 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 699 tokens, a 91% 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 32 catalogued Toofi Dental Planning MCP tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Toofi Dental Planning MCP 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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