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The MLB Stats Server MCP server costs 7,924 tokens before the first call.

Connect MLB Stats Server and its 46 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 MLB Stats Server MCP server's tool definitions consume 7,924 tokens — 4.2× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 46 tools · 7,924 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: MLB Stats Server ranks #331 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 7,924 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 172 tokens per tool.

ToolCategoryTokens% of server
get_statcast_data Read 419 5.3%
get_statcast_pitcher_pitch_arsenal Read 368 4.6%
create_spraychart_plot Write 351 4.4%
get_statcast_pitcher_data Read 326 4.1%
get_statcast_batter_data Read 325 4.1%
get_statcast_pitcher_exitvelo_barrels Read 292 3.7%
get_statcast_batter_exitvelo_barrels Read 290 3.7%
get_statcast_pitcher_expected_stats Read 288 3.6%
get_statcast_batter_expected_stats Read 283 3.6%
create_strike_zone_plot Write 282 3.6%
get_statcast_batter_pitch_arsenal Read 280 3.5%
get_statcast_pitcher_percentile_ranks Read 251 3.2%
get_schedule Read 246 3.1%
get_pitching_stats Read 228 2.9%
get_statcast_single_game Read 220 2.8%
get_statcast_batter_percentile_ranks Read 205 2.6%
create_teams_plot Write 196 2.5%
get_team_fielding Read 194 2.4%
get_team_batting Read 189 2.4%
get_team_pitching Read 189 2.4%
get_league_leader_data Read 178 2.2%
get_playerid_lookup Read 177 2.2%
get_top_prospects Read 174 2.2%
get_schedule_and_record Read 162 2.0%
reverse_lookup_player Read 154 1.9%
get_player_splits Read 142 1.8%
get_standings Read 133 1.7%
get_team_leaders Read 133 1.7%
create_bb_profile_plot Write 124 1.6%
get_meta Read 114 1.4%
get_player_stats Read 106 1.3%
get_pitching_stats_range Read 105 1.3%
get_pybaseball_standings Read 97 1.2%
get_team_roster Read 96 1.2%
get_game_scoring_play_data Read 80 1.0%
get_pitching_stats_bref Read 76 1.0%
get_boxscore Read 67 0.8%
get_game_pace Read 61 0.8%
get_last_game Read 48 0.6%
get_game_highlight_data Read 44 0.6%
get_linescore Read 42 0.5%
get_next_game Read 42 0.5%
lookup_player Read 42 0.5%
get_stats Read 41 0.5%
get_notes Read 35 0.4%
get_available_endpoints Read 29 0.4%

Most agents use a handful of these tools. They pay for all 46.

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 (172 tokens each).

Grant scopeDefinition costReduction
All 46 tools (no gateway) 7,924 tokens
3 granted tools ~517 tokens −93%
5 granted tools ~861 tokens −89%
10 granted tools ~1,723 tokens −78%

MLB Stats Server token-cost questions.

How many tokens does the MLB Stats Server MCP server use?+

Its 46 tool definitions total 7,924 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 MLB Stats Server 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 MLB Stats Server's token usage?+

Expose fewer tools. A PolicyLayer grant scopes MLB Stats Server 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 517 tokens, a 93% 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 46 catalogued MLB Stats Server tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes MLB Stats Server 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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