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The Launch Engine MCP server costs 3,910 tokens before the first call.

Connect Launch Engine and its 45 tool definitions are loaded into the model's context on every request — 2.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Launch Engine MCP server's tool definitions consume 3,910 tokens — 2.1× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 45 tools · 3,910 tokens · 2.0% 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 2.0%
1M WINDOW 0.4%

Corpus context: Launch Engine ranks #1166 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 3,910 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 87 tokens per tool.

ToolCategoryTokens% of server
capture_learning Read 266 6.8%
update_pipeline_state Write 237 6.1%
save_asset Write 138 3.5%
lessons Read 137 3.5%
rapid_test Read 114 2.9%
scout Read 102 2.6%
content_repurpose Read 97 2.5%
tournament Read 93 2.4%
content_engine Read 85 2.2%
seo_check Read 82 2.1%
bold_action Destructive 81 2.1%
passive_check Read 81 2.1%
portfolio_triage Read 81 2.1%
stress_test Read 81 2.1%
rapid_status Read 79 2.0%
validate_decide Read 79 2.0%
autonomy Read 78 2.0%
rapid_graduate Read 78 2.0%
unit_economics Read 78 2.0%
passive_deploy Execute 77 2.0%
research Read 76 1.9%
build_blocks Execute 75 1.9%
daily_check Read 75 1.9%
passive_compound Read 74 1.9%
qa Read 74 1.9%
validate_check Read 74 1.9%
voice_extract Read 74 1.9%
name_lock Write 74 1.9%
deploy Execute 73 1.9%
funnel_optimize Read 73 1.9%
market_intel Read 73 1.9%
rapid_check Read 73 1.9%
validate_prep Read 73 1.9%
dream_100 Read 72 1.8%
passive_portfolio Read 72 1.8%
channels Read 71 1.8%
platform Read 71 1.8%
creative_test Read 70 1.8%
traffic_analytics Read 70 1.8%
feedback Read 69 1.8%
product Read 69 1.8%
traffic_strategy Read 69 1.8%
scale Execute 68 1.7%
revenue_review Read 54 1.4%
status Read 50 1.3%

Most agents use a handful of these tools. They pay for all 45.

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 (87 tokens each).

Grant scopeDefinition costReduction
All 45 tools (no gateway) 3,910 tokens
3 granted tools ~261 tokens −93%
5 granted tools ~434 tokens −89%
10 granted tools ~869 tokens −78%

Launch Engine token-cost questions.

How many tokens does the Launch Engine MCP server use?+

Its 45 tool definitions total 3,910 tokens — 2.0% 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 Launch Engine 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 Launch Engine's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Launch Engine 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 261 tokens, a 93% 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 45 catalogued Launch Engine tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Launch Engine 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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