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The GitHub API MCP Server MCP server costs 2,701 tokens before the first call.

Connect GitHub API MCP Server and its 26 tool definitions are loaded into the model's context on every request — 1.4% of a 200k window spent before your agent does anything.

QUICK ANSWER The GitHub API MCP Server MCP server's tool definitions consume 2,701 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 26 tools · 2,701 tokens · 1.4% 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 1.4%
1M WINDOW 0.3%

Corpus context: GitHub API MCP Server ranks #1366 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 2,701 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 104 tokens per tool.

ToolCategoryTokens% of server
create_pull_request_review Write 231 8.6%
list_pull_requests Read 199 7.4%
create_pull_request Write 167 6.2%
push_files Write 145 5.4%
create_or_update_file Write 143 5.3%
merge_pull_request Write 129 4.8%
search_issues Read 128 4.7%
list_issues Read 124 4.6%
update_issue Write 113 4.2%
create_branch Write 98 3.6%
update_pull_request_branch Write 98 3.6%
get_file_contents Read 92 3.4%
create_issue Write 91 3.4%
search_repositories Read 90 3.3%
search_users Read 87 3.2%
create_repository Write 82 3.0%
fork_repository Read 81 3.0%
get_pull_request_status Read 75 2.8%
get_pull_request_files Read 73 2.7%
search_code Read 72 2.7%
get_pull_request_comments Read 71 2.6%
get_pull_request_reviews Read 70 2.6%
get_pull_request Read 69 2.6%
list_commits Read 67 2.5%
add_issue_comment Write 55 2.0%
get_issue Read 51 1.9%

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 (104 tokens each).

Grant scopeDefinition costReduction
All 26 tools (no gateway) 2,701 tokens
3 granted tools ~312 tokens −88%
5 granted tools ~519 tokens −81%
10 granted tools ~1,039 tokens −62%

GitHub API MCP Server token-cost questions.

How many tokens does the GitHub API MCP Server MCP server use?+

Its 26 tool definitions total 2,701 tokens — 1.4% 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 API MCP 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 GitHub API MCP Server's token usage?+

Expose fewer tools. A PolicyLayer grant scopes GitHub API MCP 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 312 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 API MCP Server tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes GitHub API MCP 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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