// MCP TOKEN COST

The Livedatalink MCP server costs 30,602 tokens before the first call.

Connect Livedatalink and its 177 tool definitions are loaded into the model's context on every request — 15% of a 200k window spent before your agent does anything.

QUICK ANSWER The Livedatalink MCP server's tool definitions consume 30,602 tokens — 16× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 177 tools · 30,602 tokens · 15% of 200k · 3.1% 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 15%

1M WINDOW 3.1%

Corpus context: Livedatalink ranks #26 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 30,602 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 173 tokens per tool.

Tool	Category	Tokens	% of server
search_available_datasets	Read	439	1.4%
fred_quick_indicator	Read	387	1.3%
census_business	Read	358	1.2%
nrel_pvwatts	Read	348	1.1%
census_demographics	Read	337	1.1%
census_population	Read	335	1.1%
fred_observations	Read	333	1.1%
census_income_housing	Read	331	1.1%
census_commute_employment	Read	322	1.1%
eia_electricity_state	Read	286	0.9%
epa_facility_search	Read	280	0.9%
nrel_alt_fuel_stations	Read	276	0.9%
reg_search	Read	261	0.9%
fda_drug_adverse_events	Read	260	0.8%
paper_search	Read	256	0.8%
worldbank_indicator	Read	255	0.8%
caselaw_search	Read	253	0.8%
spending_search_awards	Read	252	0.8%
local_search	Read	250	0.8%
book_search	Read	249	0.8%
eia_oil_supply	Read	247	0.8%
eia_renewable_generation	Read	245	0.8%
property_lookup	Read	243	0.8%
crypto_price	Read	242	0.8%
trials_search	Read	242	0.8%
fec_candidate_search	Read	238	0.8%
parcel_search	Read	238	0.8%
sanctions_screen_entity	Read	234	0.8%
stock_history	Read	234	0.8%
eia_gasoline_prices	Read	233	0.8%
eia_series_lookup	Read	228	0.7%
sanctions_screen_batch	Read	222	0.7%
entity_dossier	Execute	219	0.7%
bls_indicator	Read	219	0.7%
fda_drug_recalls	Read	219	0.7%
eia_energy_consumption	Read	218	0.7%
paper_fulltext_search	Read	218	0.7%
sanctions_search_alias	Read	218	0.7%
fec_committee_search	Read	217	0.7%
fda_device_510k	Read	215	0.7%
eia_natural_gas	Read	213	0.7%
earthquake_recent	Read	209	0.7%
sanctions_screen_address	Read	208	0.7%
disaster_declarations	Read	204	0.7%
paper_get_text	Read	204	0.7%
college_search	Read	203	0.7%
fda_food_recalls	Read	203	0.7%
property_search_area	Read	203	0.7%
reg_cfr_section	Read	201	0.7%
fec_independent_expenditures	Read	200	0.7%
patent_search	Read	200	0.7%
edgar_full_text_search	Read	198	0.6%
fda_device_recalls	Read	198	0.6%
fred_search	Read	198	0.6%
edgar_recent_filings	Execute	197	0.6%
fmcsa_carrier_compare	Read	197	0.6%
vehicle_recalls	Read	196	0.6%
book_fulltext_search	Read	195	0.6%
court_case_search	Read	191	0.6%
fmcsa_safety_scores	Read	191	0.6%
options_chain	Read	188	0.6%
stock_compare	Read	188	0.6%
edgar_filing_content	Read	186	0.6%
edgar_filings_by_form_type	Write	186	0.6%
edgar_company_facts	Read	185	0.6%
fred_compare	Read	184	0.6%
paper_details	Read	182	0.6%
cve_search_by_vendor	Read	180	0.6%
fmcsa_carrier_lookup	Read	180	0.6%
entity_resolve	Write	180	0.6%
crypto_compare	Read	179	0.6%
property_value_history	Read	177	0.6%
nonprofit_search_name	Read	176	0.6%
property_search_owner	Read	176	0.6%
reg_cfr_search	Read	176	0.6%
epa_water_or_air_violations	Write	175	0.6%
census_geography_lookup	Read	174	0.6%
book_get_text	Read	172	0.6%
college_trends	Read	172	0.6%
stock_quote_batch	Read	172	0.6%
vin_decode	Read	170	0.6%
weather_forecast	Read	170	0.6%
fec_candidate_financials	Read	169	0.6%
npi_search_provider	Read	169	0.6%
weather_current	Read	169	0.6%
nonprofit_search_location	Read	168	0.5%
npi_search_specialty	Read	167	0.5%
realestate_search	Read	165	0.5%
fda_drug_lookup	Read	164	0.5%
fmcsa_carrier_authority	Read	164	0.5%
worldbank_compare	Read	163	0.5%
realestate_trend	Read	162	0.5%
sanctions_get_changes	Read	161	0.5%
nfip_flood_claims	Read	159	0.5%
company_info	Read	158	0.5%
parcel_details	Read	158	0.5%
fmcsa_carrier_search	Read	157	0.5%
nws_active_alerts	Read	157	0.5%
package_track	Read	157	0.5%
stock_quote	Read	156	0.5%
caselaw_opinion_text	Read	155	0.5%
fred_category_series	Read	154	0.5%
air_quality	Read	152	0.5%
fred_releases	Read	152	0.5%
nrel_solar_resource	Read	152	0.5%
nrel_utility_rates	Read	152	0.5%
spending_recipient_summary	Read	151	0.5%
cve_recent	Read	150	0.5%
crypto_info	Read	148	0.5%
bls_series	Read	147	0.5%
epa_facility_compliance	Read	147	0.5%
npi_search_organization	Read	147	0.5%
nonprofit_details	Read	145	0.5%
nonprofit_status	Read	145	0.5%
cve_search_by_keyword	Read	142	0.5%
patent_inventor_search	Read	141	0.5%
nonprofit_lookup_ein	Read	140	0.5%
treasury_auctions	Read	140	0.5%
treasury_debt	Read	140	0.5%
epa_facility_details	Read	138	0.5%
caselaw_citation_lookup	Read	135	0.4%
edgar_company_lookup	Read	135	0.4%
parcel_sales_history	Read	134	0.4%
treasury_exchange_rates	Read	131	0.4%
epa_enforcement_search	Read	130	0.4%
reg_document	Read	130	0.4%
trials_details	Execute	129	0.4%
patent_assignee_search	Read	129	0.4%
disaster_history_summary	Read	127	0.4%
fbi_wanted	Read	127	0.4%
treasury_interest_rates	Read	126	0.4%
court_docket_lookup	Read	124	0.4%
fred_series_info	Read	124	0.4%
fec_candidate_details	Read	123	0.4%
ip_reputation	Read	123	0.4%
realestate_rents	Read	122	0.4%
realestate_home_values	Read	121	0.4%
github_repo	Read	119	0.4%
patent_recent	Execute	117	0.4%
edgar_insider_transactions	Read	117	0.4%
npm_package	Read	117	0.4%
rdap_ip	Read	115	0.4%
patent_details	Read	114	0.4%
spending_award_details	Read	114	0.4%
sanctions_get_entity	Read	113	0.4%
crypto_trending	Read	112	0.4%
flood_zone_lookup	Read	112	0.4%
rdap_domain	Write	112	0.4%
court_oral_argument_search	Read	111	0.4%
book_details	Read	110	0.4%
caselaw_case_details	Read	110	0.4%
college_metrics	Read	110	0.4%
court_opinion_search	Read	110	0.4%
cve_lookup	Read	110	0.4%
npi_lookup	Read	103	0.3%
court_recent_filings	Read	102	0.3%
hurricane_tracker	Read	101	0.3%
cwe_lookup	Read	99	0.3%
worldbank_country_profile	Read	96	0.3%
college_compare	Read	95	0.3%
college_demographics	Read	95	0.3%
pypi_package	Read	95	0.3%
nrel_alt_fuel_station_detail	Read	94	0.3%
court_citation_resolver	Read	93	0.3%
kev_status_check	Read	93	0.3%
epss_score	Read	92	0.3%
reg_cfr_titles	Read	92	0.3%
college_outcomes_by_program	Read	90	0.3%
cargo_crate	Read	89	0.3%
treasury_cash_balance	Read	89	0.3%
college_accreditation	Read	87	0.3%
court_judge_lookup	Read	87	0.3%
paper_status	Read	83	0.3%
book_status	Read	82	0.3%
realestate_status	Read	77	0.3%
parcel_coverage	Read	60	0.2%
sanctions_status_summary	Read	60	0.2%

// SCOPED GRANT

Most agents use a handful of these tools. They pay for all 177.

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 (173 tokens each).

Grant scope	Definition cost	Reduction
All 177 tools (no gateway)	30,602 tokens	—
3 granted tools	~519 tokens	−98%
5 granted tools	~864 tokens	−97%
10 granted tools	~1,729 tokens	−94%

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

//FAQ

Livedatalink token-cost questions.

How many tokens does the Livedatalink MCP server use?+

Its 177 tool definitions total 30,602 tokens — 15% 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 Livedatalink 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 Livedatalink's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Livedatalink 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 519 tokens, a 98% 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.

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 177 catalogued Livedatalink tools. Counts refresh with every site build.