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The AWS IoT SiteWise MCP Server MCP server costs 27,214 tokens before the first call.

Connect AWS IoT SiteWise MCP Server and its 71 tool definitions are loaded into the model's context on every request — 14% of a 200k window spent before your agent does anything.

QUICK ANSWER The AWS IoT SiteWise MCP Server MCP server's tool definitions consume 27,214 tokens — 25× the median MCP server (1,075 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 71 tools · 27,214 tokens · 14% of 200k · 2.7% 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 14%
1M WINDOW 2.7%

Corpus context: AWS IoT SiteWise MCP Server ranks #15 of 1,659 measured MCP servers by definition cost. The median is 1,075 tokens, p90 is 6,119, and the heaviest (Fusionauth) is 183,337 — 92% of a 200k window on its own.

Where the 27,214 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 383 tokens per tool.

ToolCategoryTokens% of server
execute_query Execute 2,487 9.1%
execute_training_action Execute 1,537 5.6%
create_anomaly_detection_model Write 1,090 4.0%
execute_inference_action Execute 983 3.6%
create_bulk_import_job Write 914 3.4%
create_metadata_transfer_job Financial 893 3.3%
list_computation_model_data_binding_usages Read 803 3.0%
describe_computation_model_execution_summary Read 733 2.7%
list_executions Read 695 2.6%
create_buffered_ingestion_job Write 667 2.5%
create_asset_model_composite_model Write 585 2.1%
list_actions Read 558 2.1%
get_interpolated_asset_property_values Read 529 1.9%
get_asset_property_aggregates Read 527 1.9%
execute_action Execute 471 1.7%
list_computation_model_resolve_to_resources Read 449 1.6%
create_asset_model Write 443 1.6%
update_asset_model Write 441 1.6%
list_bulk_import_jobs Read 432 1.6%
get_asset_property_value_history Read 431 1.6%
disassociate_assets Read 411 1.5%
create_computation_model Write 411 1.5%
associate_assets Read 410 1.5%
list_asset_model_properties Read 394 1.4%
describe_bulk_import_job Read 390 1.4%
list_associated_assets Read 387 1.4%
describe_execution Read 349 1.3%
put_storage_configuration Write 336 1.2%
update_computation_model Write 332 1.2%
describe_computation_model Read 326 1.2%
update_asset Write 323 1.2%
create_asset Write 303 1.1%
convert_unix_timestamp Write 301 1.1%
list_time_series Read 296 1.1%
list_computation_models Read 286 1.1%
describe_asset_model Read 275 1.0%
describe_action Read 258 0.9%
list_assets Read 246 0.9%
list_metadata_transfer_jobs Read 239 0.9%
delete_asset_model Destructive 233 0.9%
describe_asset Read 226 0.8%
create_bulk_import_schema Write 225 0.8%
delete_asset Destructive 224 0.8%
disassociate_time_series_from_asset_property Read 219 0.8%
associate_time_series_to_asset_property Read 216 0.8%
batch_get_asset_property_value_history Read 213 0.8%
list_asset_models Read 212 0.8%
batch_get_asset_property_aggregates Read 210 0.8%
create_timestamp_range Write 203 0.7%
delete_time_series Destructive 200 0.7%
convert_multiple_timestamps Write 197 0.7%
put_default_encryption_configuration Write 194 0.7%
update_gateway_capability_configuration Write 193 0.7%
delete_computation_model Destructive 178 0.7%
create_gateway Write 178 0.7%
describe_time_series Read 171 0.6%
list_gateways Read 168 0.6%
get_asset_property_value Read 158 0.6%
batch_get_asset_property_value Read 156 0.6%
describe_gateway_capability_configuration Read 148 0.5%
update_gateway Write 137 0.5%
batch_put_asset_property_value Write 126 0.5%
create_bulk_import_iam_role Write 119 0.4%
get_metadata_transfer_job Read 114 0.4%
put_logging_options Write 114 0.4%
cancel_metadata_transfer_job Financial 112 0.4%
delete_gateway Destructive 100 0.4%
describe_gateway Read 100 0.4%
describe_default_encryption_configuration Read 79 0.3%
describe_logging_options Read 75 0.3%
describe_storage_configuration Read 75 0.3%

Computed over 71 of 72 catalogued tools — the remainder have no published input schema, so the true total is slightly higher.

Most agents use a handful of these tools. They pay for all 71.

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 (383 tokens each).

Grant scopeDefinition costReduction
All 71 tools (no gateway) 27,214 tokens
3 granted tools ~1,150 tokens −96%
5 granted tools ~1,916 tokens −93%
10 granted tools ~3,833 tokens −86%

AWS IoT SiteWise MCP Server token-cost questions.

How many tokens does the AWS IoT SiteWise MCP Server MCP server use?+

Its 71 tool definitions total 27,214 tokens — 14% 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 AWS IoT SiteWise MCP Server 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 AWS IoT SiteWise MCP Server's token usage?+

Expose fewer tools. A PolicyLayer grant scopes AWS IoT SiteWise MCP Server 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 1,150 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.

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 05-06-2026 from the PolicyLayer scan database over 71 of 72 catalogued AWS IoT SiteWise MCP Server tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes AWS IoT SiteWise MCP Server 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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