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The Busymate DevTools MCP server costs 13,115 tokens before the first call.

Every request your agent makes carries every tool definition this server exposes — context your code, documents and conversation can't use, mostly for tools the agent never calls. You don't need them all in the window, and you don't have to pay for them.

QUICK ANSWER The Busymate DevTools MCP server's 44 tool definitions consume 13,115 tokens — 6.6% of a 200k context window, and 6.6× the median MCP server (1,986 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS tiktoken o200k_base · rank #333 of 7,317 measured servers · refreshed every build Method →

What that costs 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 6.6%
1M WINDOW 1.3%

Corpus context: Busymate DevTools ranks #333 of 7,317 measured MCP servers by definition cost. The median is 1,986 tokens, p90 is 12,223, and the heaviest (Ainumbers Mcp Apps) is 320,441 — 160% of a 200k window on its own. New to this? See MCP token cost and context window in the glossary.

Where the 13,115 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 298 tokens per tool.

ToolCategoryTokens% of server
list_device_events Read 1,939 14.8%
list_audit_events Read 1,052 8.0%
list_devices Read 965 7.4%
get_device Read 668 5.1%
list_entries Read 650 5.0%
get_device_health Read 499 3.8%
test_pac_connection Read 499 3.8%
get_entry Read 446 3.4%
inspect_requests Read 435 3.3%
summarize_device_traffic Execute 352 2.7%
list_issue_reports Read 337 2.6%
list_breakpoint_events Read 334 2.5%
list_todos Read 320 2.4%
get_device_egress_fail_posture Read 319 2.4%
get_device_egress_status Read 294 2.2%
list_advisor_findings Read 291 2.2%
search_entries Read 281 2.1%
get_my_account Read 263 2.0%
get_status Read 262 2.0%
get_audit_event Read 236 1.8%
get_usage Read 219 1.7%
share_advisor_finding Execute 210 1.6%
get_advisor_finding Read 179 1.4%
list_device_service_groups Read 179 1.4%
get_push_response Read 177 1.3%
get_block_rules_device Read 163 1.2%
list_invoices Read 149 1.1%
list_device_audit_modes Read 144 1.1%
get_device_status Read 143 1.1%
get_entry_count Read 141 1.1%
get_subscription Read 130 1.0%
list_push_tokens Read 129 1.0%
list_workspaces Read 123 0.9%
export_har Read 91 0.7%
get_todo Read 88 0.7%
download_snapshot Read 54 0.4%
list_service_groups Read 54 0.4%
get_device_settings Read 53 0.4%
list_tabs Read 51 0.4%
get_service_group Read 46 0.4%
get_workspace Read 44 0.3%
list_tags Read 37 0.3%
get_stats Read 35 0.3%
list_snapshots Read 34 0.3%

Your agent uses a handful of these tools. It pays for all 44.

You don't need all 44 of those definitions in the window. PolicyLayer is an MCP gateway that sits in front of Busymate DevTools: only the tools you grant are exposed to the agent, the rest never load. A smaller window means a sharper agent — less noise when it picks a tool — and every request costs less:

Grant scopeDefinition costReduction
All 44 tools (no gateway) 13,115 tokens
3 granted tools ~894 tokens −93%
5 granted tools ~1,490 tokens −89%
10 granted tools ~2,981 tokens −77%
  1. Create a free account and register Busymate DevTools — nothing to install.
  2. Grant only the tools you use — ungranted definitions never enter the context window.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
CUT BUSYMATE DEVTOOLS TOKEN COST →

Instant setup, no code required.

Busymate DevTools token-cost questions.

How many tokens does the Busymate DevTools MCP server use?+

Its 44 tool definitions total 13,115 tokens — 6.6% 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 Busymate DevTools 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 Busymate DevTools's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Busymate DevTools 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 894 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 23-08-2026 from the PolicyLayer scan database over all 44 catalogued Busymate DevTools tools. Counts refresh with every site build.

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

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

Instant setup, no code required.

46,500+ MCP servers and 515,000+ tools scanned and risk-classified.

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