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The AILANG Parse MCP server costs 3,423 tokens before the first call.

Connect AILANG Parse and its 31 tool definitions are loaded into the model's context on every request — 1.7% of a 200k window spent before your agent does anything.

QUICK ANSWER The AILANG Parse MCP server's tool definitions consume 3,423 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 31 tools · 3,423 tokens · 1.7% of 200k · 0.3% 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 1.7%
1M WINDOW 0.3%

Corpus context: AILANG Parse ranks #1239 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 3,423 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 110 tokens per tool.

ToolCategoryTokens% of server
submit_feedback Write 376 11.0%
parseFileSecure Execute 329 9.6%
editDocument Write 222 6.5%
partitionGeneral Destructive 171 5.0%
deviceAuthInspect Read 144 4.2%
health Read 139 4.1%
mcpParse Execute 133 3.9%
mcpAccount Read 129 3.8%
agentCard Read 123 3.6%
requestHistory Write 123 3.6%
getUploadUrl Read 118 3.4%
mcpConvert Write 109 3.2%
listApiKeys Read 102 3.0%
mcpAuth Execute 99 2.9%
requestReplay Read 97 2.8%
deviceAuthApprove Write 96 2.8%
myEntitlements Write 82 2.4%
mcpAuthPoll Read 76 2.2%
mcpFormats Read 75 2.2%
formats Read 74 2.2%
deviceAuthPoll Read 72 2.1%
mcpEstimate Read 64 1.9%
getKeyUsage Read 61 1.8%
apiSamples Read 60 1.8%
deviceAuthRequest Read 60 1.8%
estimate Read 57 1.7%
apiTools Read 54 1.6%
revokeApiKey Destructive 51 1.5%
rotateApiKey Destructive 48 1.4%
capabilities Read 42 1.2%
pricing Read 37 1.1%

Most agents use a handful of these tools. They pay for all 31.

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 (110 tokens each).

Grant scopeDefinition costReduction
All 31 tools (no gateway) 3,423 tokens
3 granted tools ~331 tokens −90%
5 granted tools ~552 tokens −84%
10 granted tools ~1,104 tokens −68%

AILANG Parse token-cost questions.

How many tokens does the AILANG Parse MCP server use?+

Its 31 tool definitions total 3,423 tokens — 1.7% 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 AILANG Parse 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 AILANG Parse's token usage?+

Expose fewer tools. A PolicyLayer grant scopes AILANG Parse 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 331 tokens, a 90% 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 31 catalogued AILANG Parse tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes AILANG Parse 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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