Home / Token cost / Name Whisper — ENS Intelligence Layer

The Name Whisper — ENS Intelligence Layer MCP server costs 13,827 tokens before the first call.

Connect Name Whisper — ENS Intelligence Layer and its 42 tool definitions are loaded into the model's context on every request — 6.9% of a 200k window spent before your agent does anything.

QUICK ANSWER The Name Whisper — ENS Intelligence Layer MCP server's tool definitions consume 13,827 tokens — 7.3× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 42 tools · 13,827 tokens · 6.9% of 200k · 1.4% 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 6.9%
1M WINDOW 1.4%

Corpus context: Name Whisper — ENS Intelligence Layer ranks #107 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 13,827 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 329 tokens per tool.

ToolCategoryTokens% of server
set_ens_records Write 780 5.6%
find_alpha Read 712 5.1%
provision_agent_identity Execute 603 4.4%
sweep Execute 581 4.2%
manage_fuses Destructive 564 4.1%
bulk_set_records Write 532 3.8%
enumerate_entities Read 525 3.8%
approve_operator Write 458 3.3%
purchase_name Read 434 3.1%
make_offer Read 432 3.1%
mint_subnames Write 431 3.1%
create_listing Write 397 2.9%
bulk_transfer_ens_names Financial 389 2.8%
renew_ens_name Read 385 2.8%
batch_create_listings Write 377 2.7%
wrap_name Destructive 353 2.6%
batch_purchase Read 351 2.5%
bulk_register Write 342 2.5%
cancel_listing Destructive 335 2.4%
search_agent_directory Read 312 2.3%
manage_ens_name Write 311 2.2%
cancel_offer Destructive 310 2.2%
accept_offer Execute 299 2.2%
transfer_ens_name Financial 281 2.0%
set_resolver Write 257 1.9%
search_knowledge Read 243 1.8%
extend_subname_expiry Write 226 1.6%
get_name_details Read 221 1.6%
set_primary_name Write 219 1.6%
search_ens_names Read 212 1.5%
unwrap_name Read 211 1.5%
reclaim_name Write 209 1.5%
wash_check Read 197 1.4%
get_primary_name Read 195 1.4%
get_agent_reputation Read 184 1.3%
get_market_activity Read 182 1.3%
get_wallet_portfolio Read 162 1.2%
get_similar_names Read 160 1.2%
check_availability Read 156 1.1%
get_valuation Read 135 1.0%
get_caller_identity Read 107 0.8%
get_usage_stats Read 57 0.4%

Most agents use a handful of these tools. They pay for all 42.

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 (329 tokens each).

Grant scopeDefinition costReduction
All 42 tools (no gateway) 13,827 tokens
3 granted tools ~988 tokens −93%
5 granted tools ~1,646 tokens −88%
10 granted tools ~3,292 tokens −76%

Name Whisper — ENS Intelligence Layer token-cost questions.

How many tokens does the Name Whisper — ENS Intelligence Layer MCP server use?+

Its 42 tool definitions total 13,827 tokens — 6.9% 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 Name Whisper — ENS Intelligence Layer 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 Name Whisper — ENS Intelligence Layer's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Name Whisper — ENS Intelligence Layer 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 988 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 42 catalogued Name Whisper — ENS Intelligence Layer tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Name Whisper — ENS Intelligence Layer 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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