// MCP TOKEN COST

The lilo Vacation Rentals MCP server costs 8,683 tokens before the first call.

Connect lilo Vacation Rentals and its 67 tool definitions are loaded into the model's context on every request — 4.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The lilo Vacation Rentals MCP server's tool definitions consume 8,683 tokens — 4.6× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 67 tools · 8,683 tokens · 4.3% of 200k · 0.9% of 1M Method →

// CONTEXT WINDOW SHARE

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 4.3%

1M WINDOW 0.9%

Corpus context: lilo Vacation Rentals ranks #210 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.

// PER-TOOL BREAKDOWN

Where the 8,683 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 130 tokens per tool.

Tool	Category	Tokens	% of server
verify_rental_checkout_condition	Read	248	2.9%
book_vacation_rental_direct	Read	247	2.8%
create_rental_maintenance_task	Write	242	2.8%
screen_guest_before_booking	Read	236	2.7%
search_world_cup_rentals	Read	228	2.6%
search_vacation_rentals	Read	215	2.5%
report_rental_inventory_issue	Write	194	2.2%
search_vacation_rental_market	Read	188	2.2%
verify_guest_identity_for_check_in	Read	186	2.1%
check_vacation_rental_availability_and_pricing	Read	174	2.0%
record_guest_interaction_to_evidence	Read	173	2.0%
search_vacation_rentals_by_description	Read	172	2.0%
search_vacation_rentals_by_location	Read	163	1.9%
detect_guest_communication_risk	Read	157	1.8%
assign_cleaner_to_rental_turnover	Write	154	1.8%
ask_vacation_rental_question	Read	153	1.8%
assess_extended_stay_squatter_risk	Read	151	1.7%
analyze_guest_communication_risk	Read	148	1.7%
search_philadelphia_historic_properties	Read	139	1.6%
get_vacation_rental_faqs	Read	137	1.6%
get_vacation_rental_inventory	Read	135	1.6%
get_rental_maintenance_schedule	Read	133	1.5%
get_evidence_timeline_for_rental	Read	131	1.5%
flag_booking_for_enhanced_monitoring	Read	130	1.5%
verify_vacation_rental_trust_chain	Read	130	1.5%
get_short_term_rental_regulations	Read	128	1.5%
get_vacation_rental_onboarding_status	Read	128	1.5%
query_vacation_rental_evidence_chain	Read	127	1.5%
get_philadelphia_landmark_details	Read	125	1.4%
forecast_vacation_rental_demand	Read	123	1.4%
get_chargeback_defense_for_booking	Read	122	1.4%
search_vacation_rentals_by_amenities	Read	119	1.4%
generate_str_tax_documentation	Write	118	1.4%
detect_guest_message_threat_pattern	Read	114	1.3%
find_similar_vacation_rentals	Read	114	1.3%
get_dispute_evidence_bundle_for_booking	Read	114	1.3%
get_vacation_rental_pricing_analysis	Read	114	1.3%
generate_google_vacation_rentals_feed	Write	114	1.3%
predict_booking_chargeback_probability	Read	113	1.3%
search_philadelphia_event_venues	Read	113	1.3%
analyze_booking_threat_risk	Read	112	1.3%
check_world_cup_2026_str_compliance	Read	112	1.3%
analyze_guest_interaction_risk	Read	109	1.3%
assess_vacation_rental_booking_risk	Read	109	1.3%
fetch_vacation_rental_details	Read	109	1.3%
get_local_recommendations_near_rental	Read	109	1.3%
get_vacation_rental_ai_manifest	Read	108	1.2%
get_vacation_rental_details	Read	108	1.2%
check_str_permit_requirements	Read	106	1.2%
get_rental_cleaning_schedule	Read	104	1.2%
get_dispute_defense_packet_for_booking	Read	102	1.2%
get_vacation_rental_trust_certificate	Read	102	1.2%
get_str_insurance_requirements	Read	101	1.2%
ingest_philadelphia_public_records	Read	99	1.1%
compare_vacation_rentals_side_by_side	Read	97	1.1%
get_vacation_rental_reputation_score	Read	93	1.1%
verify_evidence_anchor_integrity	Read	93	1.1%
verify_vacation_rental_evidence_record	Read	88	1.0%
get_vacation_rental_house_rules	Read	85	1.0%
get_vacation_rental_host_reputation	Read	82	0.9%
check_vacation_rental_protection_status	Read	79	0.9%
get_neighborhood_info_for_rental	Read	79	0.9%
get_philadelphia_250th_anniversary_events	Read	76	0.9%
get_vacation_rental_identity_manifest	Read	73	0.8%
get_lilo_founding_member_availability	Read	71	0.8%
get_philadelphia_world_cup_2026_info	Read	70	0.8%
get_lilo_protection_network_stats	Read	57	0.7%

// SCOPED GRANT

Most agents use a handful of these tools. They pay for all 67.

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 (130 tokens each).

Grant scope	Definition cost	Reduction
All 67 tools (no gateway)	8,683 tokens	—
3 granted tools	~389 tokens	−96%
5 granted tools	~648 tokens	−93%
10 granted tools	~1,296 tokens	−85%

Model your own stack in the token-cost calculator, or see the lilo Vacation Rentals policy for what a sensible grant looks like.

//FAQ

lilo Vacation Rentals token-cost questions.

How many tokens does the lilo Vacation Rentals MCP server use?+

Its 67 tool definitions total 8,683 tokens — 4.3% 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 lilo Vacation Rentals 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 lilo Vacation Rentals's token usage?+

Expose fewer tools. A PolicyLayer grant scopes lilo Vacation Rentals 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 389 tokens, a 96% 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.

// METHOD & REVIEW

How these numbers were measured.

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.

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.

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 67 catalogued lilo Vacation Rentals tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes lilo Vacation Rentals to the tools you actually allow. Ungranted definitions never load, and every call that does run is checked against policy first.

SCOPE YOUR GRANT →

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