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The Github_private MCP server costs 7,938 tokens before the first call.

Connect Github_private and its 26 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 Github_private MCP server's tool definitions consume 7,938 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 26 tools · 7,938 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: Github_private ranks #327 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 7,938 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 305 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 3.8%
resolve_entity Write 289 3.6%
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%
gh_list_issues Read 170 2.1%
gh_list_pulls Read 170 2.1%
remember Destructive 168 2.1%
gh_get_file Read 163 2.1%
recall Destructive 130 1.6%
gh_list_repos Read 127 1.6%
gh_get_repo Read 91 1.1%
forget Destructive 83 1.0%
gh_list_orgs Read 50 0.6%

Most agents use a handful of these tools. They pay for all 26.

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 (305 tokens each).

Grant scopeDefinition costReduction
All 26 tools (no gateway) 7,938 tokens
3 granted tools ~916 tokens −88%
5 granted tools ~1,527 tokens −81%
10 granted tools ~3,053 tokens −62%

Github_private token-cost questions.

How many tokens does the Github_private MCP server use?+

Its 26 tool definitions total 7,938 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 Github_private 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 Github_private's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Github_private 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 916 tokens, a 88% 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 26 catalogued Github_private tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Github_private 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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