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The Atlas Pipeline MCP server costs 6,447 tokens before the first call.

Connect Atlas Pipeline and its 31 tool definitions are loaded into the model's context on every request — 3.2% of a 200k window spent before your agent does anything.

QUICK ANSWER The Atlas Pipeline MCP server's tool definitions consume 6,447 tokens — 3.4× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 31 tools · 6,447 tokens · 3.2% of 200k · 0.6% 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 3.2%
1M WINDOW 0.6%

Corpus context: Atlas Pipeline ranks #936 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 6,447 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 208 tokens per tool.

ToolCategoryTokens% of server
atlas_think Read 511 7.9%
atlas_code_whisperer Read 431 6.7%
atlas_codebase_surgeon Execute 355 5.5%
atlas_semantic_search Read 341 5.3%
atlas_bug_oracle Read 331 5.1%
atlas_api_helper Read 305 4.7%
atlas_refactor Read 286 4.4%
atlas_review Read 274 4.3%
atlas_profiler Read 263 4.1%
atlas_smart_merge Write 255 4.0%
atlas_animation_studio Read 253 3.9%
atlas_tech_debt_quantifier Read 245 3.8%
atlas_ui_ux_designer Read 241 3.7%
atlas_dashboard Read 222 3.4%
atlas_test Read 185 2.9%
atlas_docs Read 182 2.8%
atlas_explain Read 175 2.7%
atlas_performance_doctor Execute 173 2.7%
atlas_css_wizard Read 168 2.6%
atlas_dependencies Read 166 2.6%
atlas_debug Read 136 2.1%
atlas_security Read 118 1.8%
atlas_pipeline Execute 110 1.7%
atlas_intent Read 104 1.6%
atlas_variants Read 102 1.6%
atlas_critique Read 99 1.5%
atlas_git Read 97 1.5%
atlas_context Read 96 1.5%
atlas_optimize Read 96 1.5%
atlas_decompose Read 94 1.5%
atlas_providers Read 33 0.5%

Most agents use a handful of these tools. They pay for all 31.

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 (208 tokens each).

Grant scopeDefinition costReduction
All 31 tools (no gateway) 6,447 tokens
3 granted tools ~624 tokens −90%
5 granted tools ~1,040 tokens −84%
10 granted tools ~2,080 tokens −68%

Atlas Pipeline token-cost questions.

How many tokens does the Atlas Pipeline MCP server use?+

Its 31 tool definitions total 6,447 tokens — 3.2% 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 Atlas Pipeline 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 Atlas Pipeline's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Atlas Pipeline 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 624 tokens, a 90% 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 31 catalogued Atlas Pipeline tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Atlas Pipeline 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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