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The Garl Protocol MCP server costs 3,651 tokens before the first call.

Connect Garl Protocol and its 28 tool definitions are loaded into the model's context on every request — 1.8% of a 200k window spent before your agent does anything.

QUICK ANSWER The Garl Protocol MCP server's tool definitions consume 3,651 tokens — around the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 28 tools · 3,651 tokens · 1.8% of 200k · 0.4% 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 1.8%
1M WINDOW 0.4%

Corpus context: Garl Protocol ranks #1196 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 3,651 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 130 tokens per tool.

ToolCategoryTokens% of server
garl_record_action_receipt Destructive 465 12.7%
garl_verify Read 308 8.4%
garl_evaluate_action Read 240 6.6%
garl_issue_capability_token Write 224 6.1%
garl_should_delegate Destructive 195 5.3%
garl_receipt Read 159 4.4%
garl_trust_gate Read 155 4.2%
garl_register_agent Write 153 4.2%
garl_simulate_score Read 152 4.2%
garl_verify_batch Read 122 3.3%
garl_route Read 116 3.2%
garl_get_trust_vector Read 109 3.0%
garl_search Read 103 2.8%
garl_leaderboard Read 99 2.7%
garl_revoke_capability_token Destructive 98 2.7%
garl_endorse Read 95 2.6%
garl_register_webhook Write 95 2.6%
garl_undo_action Destructive 94 2.6%
garl_verify_capability_token Read 85 2.3%
garl_trust_history Read 79 2.2%
garl_compare Read 75 2.1%
garl_check_trust Read 69 1.9%
garl_anonymize Read 63 1.7%
garl_get_feed Read 63 1.7%
garl_soft_delete Destructive 61 1.7%
garl_compliance Read 61 1.7%
garl_agent_card Read 59 1.6%
garl_get_score Read 54 1.5%

Most agents use a handful of these tools. They pay for all 28.

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 (130 tokens each).

Grant scopeDefinition costReduction
All 28 tools (no gateway) 3,651 tokens
3 granted tools ~391 tokens −89%
5 granted tools ~652 tokens −82%
10 granted tools ~1,304 tokens −64%

Garl Protocol token-cost questions.

How many tokens does the Garl Protocol MCP server use?+

Its 28 tool definitions total 3,651 tokens — 1.8% 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 Garl Protocol 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 Garl Protocol's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Garl Protocol 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 391 tokens, a 89% 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 28 catalogued Garl Protocol tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Garl Protocol 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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