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The Unsplash MCP server costs 7,901 tokens before the first call.

Connect Unsplash and its 35 tool definitions are loaded into the model's context on every request — 4.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Unsplash MCP server's tool definitions consume 7,901 tokens — 4.1× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 35 tools · 7,901 tokens · 4.0% of 200k · 0.8% 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 4.0%
1M WINDOW 0.8%

Corpus context: Unsplash ranks #347 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 7,901 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 226 tokens per tool.

ToolCategoryTokens% of server
polymarket_edges Destructive 1,070 13.5%
bet_research Read 967 12.2%
polymarket_kalshi_spread Read 588 7.4%
polymarket_arbitrage Read 390 4.9%
ask_pipeworx Read 359 4.5%
recent_changes Read 359 4.5%
entity_profile Read 347 4.4%
pipeworx_feedback Read 327 4.1%
discover_tools Write 316 4.0%
compare_entities Read 315 4.0%
ai_visibility_check Read 305 3.9%
resolve_entity Write 289 3.7%
scan_dependency Read 278 3.5%
scan_competitor_ai_presence Read 269 3.4%
validate_claim Read 225 2.8%
pipeworx_trending Read 197 2.5%
generate_llms_txt Write 185 2.3%
remember Destructive 168 2.1%
recall Destructive 130 1.6%
forget Destructive 83 1.1%
photo_statistics Read 82 1.0%
collection_photos Read 65 0.8%
topic_photos Read 59 0.7%
user_likes Read 57 0.7%
user_photos Read 57 0.7%
search_photos Read 53 0.7%
photo_download Read 47 0.6%
collection Read 46 0.6%
photo Read 45 0.6%
topic Read 45 0.6%
user Read 42 0.5%
list_photos Read 38 0.5%
photo_random Read 34 0.4%
collections Read 32 0.4%
topics Read 32 0.4%

Most agents use a handful of these tools. They pay for all 35.

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 (226 tokens each).

Grant scopeDefinition costReduction
All 35 tools (no gateway) 7,901 tokens
3 granted tools ~677 tokens −91%
5 granted tools ~1,129 tokens −86%
10 granted tools ~2,257 tokens −71%

Unsplash token-cost questions.

How many tokens does the Unsplash MCP server use?+

Its 35 tool definitions total 7,901 tokens — 4.0% 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 Unsplash 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 Unsplash's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Unsplash 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 677 tokens, a 91% 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 35 catalogued Unsplash tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Unsplash 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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