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The PingZen Uptime Monitoring MCP server costs 4,664 tokens before the first call.

Connect PingZen Uptime Monitoring and its 44 tool definitions are loaded into the model's context on every request — 2.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The PingZen Uptime Monitoring MCP server's tool definitions consume 4,664 tokens — 2.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 44 tools · 4,664 tokens · 2.3% of 200k · 0.5% 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 2.3%
1M WINDOW 0.5%

Corpus context: PingZen Uptime Monitoring ranks #1069 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 4,664 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 106 tokens per tool.

ToolCategoryTokens% of server
create_monitor Write 287 6.2%
create_alert Write 235 5.0%
create_heartbeat Write 197 4.2%
create_status_page Write 177 3.8%
update_monitor Write 173 3.7%
get_check_history Read 171 3.7%
update_alert Write 160 3.4%
get_uptime_stats Read 146 3.1%
list_monitors Read 146 3.1%
register Write 146 3.1%
update_status_page Write 136 2.9%
generate_api_key Write 135 2.9%
login Write 135 2.9%
get_monitor_status Read 128 2.7%
execute_check Execute 116 2.5%
delete_monitor Destructive 113 2.4%
update_monitor_group Write 111 2.4%
create_monitor_group Write 109 2.3%
create_workspace Write 107 2.3%
link_telegram_group Write 105 2.3%
list_incidents Read 103 2.2%
update_incident Write 97 2.1%
list_heartbeats Read 95 2.0%
add_status_page_monitor Write 92 2.0%
delete_telegram_group Destructive 90 1.9%
update_workspace Write 87 1.9%
list_alerts Read 86 1.8%
delete_heartbeat Destructive 84 1.8%
refresh_token Write 82 1.8%
delete_monitor_group Destructive 79 1.7%
list_telegram_groups Read 77 1.7%
get_heartbeat Read 70 1.5%
delete_alert Destructive 60 1.3%
get_current_user Read 58 1.2%
pause_heartbeat Write 58 1.2%
resolve_incident Write 58 1.2%
remove_status_page_monitor Destructive 57 1.2%
resume_heartbeat Write 54 1.2%
list_monitor_groups Read 52 1.1%
ping Write 47 1.0%
test_alert Read 45 1.0%
get_incident Read 41 0.9%
list_workspaces Read 30 0.6%
list_status_pages Read 29 0.6%

Most agents use a handful of these tools. They pay for all 44.

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 (106 tokens each).

Grant scopeDefinition costReduction
All 44 tools (no gateway) 4,664 tokens
3 granted tools ~318 tokens −93%
5 granted tools ~530 tokens −89%
10 granted tools ~1,060 tokens −77%

PingZen Uptime Monitoring token-cost questions.

How many tokens does the PingZen Uptime Monitoring MCP server use?+

Its 44 tool definitions total 4,664 tokens — 2.3% 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 PingZen Uptime Monitoring 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 PingZen Uptime Monitoring's token usage?+

Expose fewer tools. A PolicyLayer grant scopes PingZen Uptime Monitoring 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 318 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 44 catalogued PingZen Uptime Monitoring tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes PingZen Uptime Monitoring 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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