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The Chessagine MCP server costs 4,214 tokens before the first call.

Connect Chessagine and its 37 tool definitions are loaded into the model's context on every request — 2.1% of a 200k window spent before your agent does anything.

QUICK ANSWER The Chessagine MCP server's tool definitions consume 4,214 tokens — 2.2× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 37 tools · 4,214 tokens · 2.1% 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 2.1%
1M WINDOW 0.4%

Corpus context: Chessagine ranks #1114 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 4,214 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 114 tokens per tool.

ToolCategoryTokens% of server
get-maia2-analysis Read 227 5.4%
get-stockfish-multipv-analysis Read 199 4.7%
get-stockfish-batch-analysis Read 172 4.1%
get-elite-leela-analysis Read 166 3.9%
get-stockfish-best-move Read 165 3.9%
get-boardstate-for-move Read 163 3.9%
get-stockfish-analysis Read 159 3.8%
get-leela-analysis Read 157 3.7%
render_chess_board Read 150 3.6%
fetch-chess-puzzle Read 144 3.4%
fen-openingbook-lookup Read 140 3.3%
get-chessboardmagic-tcec-stats Read 139 3.3%
get-boardstate-for-fen Read 138 3.3%
get-lichess-master-games Read 136 3.2%
get-chessdb-pv Read 135 3.2%
get-chessboardmagic-corr-games Read 133 3.2%
get-chessboardmagic-corr-stats Read 133 3.2%
get-chessboardmagic-tcec-games Read 133 3.2%
get-lichess-games Read 133 3.2%
queue-chessdb-analysis Read 130 3.1%
get-chessdb-analysis Read 129 3.1%
fetch-lichess-game Read 106 2.5%
fetch-lichess-study-pgn Read 99 2.3%
render_pgn_viewer Read 93 2.2%
is-legal-move Read 87 2.1%
fetch-lichess-games Read 83 2.0%
get-fen-map-lookup Read 82 1.9%
fetch-lichess-studies Read 79 1.9%
get-chessboardmagic-repertoire-details Read 59 1.4%
get-chessboardmagic-game-details Read 56 1.3%
get-chess-knowledgebase Read 52 1.2%
parse-pgn-into-fens Execute 46 1.1%
get-chessboardmagic-repertoires Read 42 1.0%
get-puzzle-themes Read 39 0.9%
get-chessagine-stater-prompts Read 38 0.9%
get-chessboardmagic-games Read 37 0.9%
get-lichess-username Read 35 0.8%

Most agents use a handful of these tools. They pay for all 37.

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 (114 tokens each).

Grant scopeDefinition costReduction
All 37 tools (no gateway) 4,214 tokens
3 granted tools ~342 tokens −92%
5 granted tools ~569 tokens −86%
10 granted tools ~1,139 tokens −73%

Chessagine token-cost questions.

How many tokens does the Chessagine MCP server use?+

Its 37 tool definitions total 4,214 tokens — 2.1% 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 Chessagine 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 Chessagine's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Chessagine 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 342 tokens, a 92% 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 37 catalogued Chessagine tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Chessagine 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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