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The Loopctl MCP server costs 6,507 tokens before the first call.

Connect Loopctl and its 52 tool definitions are loaded into the model's context on every request — 3.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The Loopctl MCP server's tool definitions consume 6,507 tokens — 3.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 52 tools · 6,507 tokens · 3.3% of 200k · 0.7% 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 3.3%
1M WINDOW 0.7%

Corpus context: Loopctl ranks #933 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 6,507 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 125 tokens per tool.

ToolCategoryTokens% of server
backfill_story Write 270 4.1%
knowledge_ingest_batch Read 269 4.1%
report_token_usage Read 257 3.9%
list_stories Read 241 3.7%
report_story Read 237 3.6%
import_stories Write 222 3.4%
create_story Write 217 3.3%
knowledge_lint Execute 211 3.2%
review_complete Write 194 3.0%
knowledge_search Read 192 3.0%
set_token_budget Write 192 3.0%
knowledge_agent_usage Read 190 2.9%
dispatch Read 186 2.9%
knowledge_context Read 175 2.7%
knowledge_ingest Read 168 2.6%
create_project Write 148 2.3%
bulk_mark_complete Write 136 2.1%
knowledge_analytics_top Read 135 2.1%
knowledge_drafts Read 131 2.0%
knowledge_create Write 131 2.0%
contract_story Read 127 2.0%
knowledge_bulk_publish Write 125 1.9%
verify_all_in_epic Read 123 1.9%
knowledge_get Read 122 1.9%
recover_cap Read 113 1.7%
knowledge_delete Destructive 108 1.7%
verify_story Read 107 1.6%
knowledge_unused_articles Read 105 1.6%
knowledge_index Execute 101 1.6%
knowledge_archive Write 100 1.5%
knowledge_unpublish Destructive 99 1.5%
get_cost_summary Read 99 1.5%
delete_project Destructive 98 1.5%
list_ready_stories Read 98 1.5%
get_progress Read 85 1.3%
reject_story Write 83 1.3%
get_system_articles Read 77 1.2%
knowledge_export Write 75 1.2%
knowledge_article_stats Read 73 1.1%
request_review Read 72 1.1%
claim_story Read 68 1.0%
get_cost_anomalies Read 64 1.0%
knowledge_publish Write 61 0.9%
start_story Execute 60 0.9%
get_sth Read 57 0.9%
knowledge_ingestion_jobs Read 54 0.8%
get_acceptance_criteria Read 51 0.8%
get_story_token_usage Read 51 0.8%
get_story Read 50 0.8%
get_tenant Read 34 0.5%
list_routes Read 34 0.5%
list_projects Read 31 0.5%

Most agents use a handful of these tools. They pay for all 52.

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 (125 tokens each).

Grant scopeDefinition costReduction
All 52 tools (no gateway) 6,507 tokens
3 granted tools ~375 tokens −94%
5 granted tools ~626 tokens −90%
10 granted tools ~1,251 tokens −81%

Loopctl token-cost questions.

How many tokens does the Loopctl MCP server use?+

Its 52 tool definitions total 6,507 tokens — 3.3% 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 Loopctl 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 Loopctl's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Loopctl 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 375 tokens, a 94% 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 52 catalogued Loopctl tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Loopctl 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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