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The ContextLayer MCP server costs 9,531 tokens before the first call.

Connect ContextLayer and its 62 tool definitions are loaded into the model's context on every request — 4.8% of a 200k window spent before your agent does anything.

QUICK ANSWER The ContextLayer MCP server's tool definitions consume 9,531 tokens — 5.0× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 62 tools · 9,531 tokens · 4.8% of 200k · 1.0% 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 4.8%
1M WINDOW 1.0%

Corpus context: ContextLayer ranks #182 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 9,531 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 154 tokens per tool.

ToolCategoryTokens% of server
upload_document Write 477 5.0%
setup_organization Write 424 4.4%
create_task Write 408 4.3%
log_traces_batch Read 387 4.1%
log_trace Read 336 3.5%
update_task Write 297 3.1%
start_session Execute 262 2.7%
log_activity Execute 251 2.6%
get_context Read 238 2.5%
list_tasks Read 210 2.2%
find_documents Read 209 2.2%
update_org Write 208 2.2%
add_task_dependency Write 195 2.0%
invite_user Write 188 2.0%
update_position Write 188 2.0%
update_user Write 180 1.9%
update_project Write 178 1.9%
update_team Write 171 1.8%
create_sprint Write 168 1.8%
end_session Read 163 1.7%
get_live_activity Read 160 1.7%
add_team_member Write 159 1.7%
unlink_team_project Read 153 1.6%
move_task_to_sprint Write 153 1.6%
link_team_project Read 152 1.6%
search_entities Read 149 1.6%
create_position Write 142 1.5%
list_sessions Read 137 1.4%
remove_team_member Destructive 134 1.4%
set_context_routing Write 132 1.4%
list_colleagues Read 130 1.4%
create_team Write 122 1.3%
get_team_details Read 115 1.2%
get_document Read 113 1.2%
list_notifications Read 113 1.2%
get_session_details Read 112 1.2%
link_task_session Read 112 1.2%
get_project_status Read 111 1.2%
mark_notification_read Write 107 1.1%
assign_task Write 106 1.1%
list_project_members Read 105 1.1%
list_sprints Read 105 1.1%
remove_task_dependency Destructive 104 1.1%
delete_position Destructive 102 1.1%
delete_project Destructive 102 1.1%
delete_team Destructive 102 1.1%
unassign_task Destructive 94 1.0%
create_project Write 92 1.0%
list_project_teams Read 88 0.9%
remove_user_from_org Destructive 85 0.9%
list_projects Read 83 0.9%
delete_user Destructive 78 0.8%
delete_task Destructive 77 0.8%
accept_org_invite Write 76 0.8%
delete_document Destructive 75 0.8%
whoami Read 71 0.7%
get_context_routing Read 68 0.7%
get_my_stats Read 61 0.6%
list_teams Read 58 0.6%
get_org_stats Read 53 0.6%
list_pending_invites Read 51 0.5%
list_positions Read 51 0.5%

Most agents use a handful of these tools. They pay for all 62.

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 (154 tokens each).

Grant scopeDefinition costReduction
All 62 tools (no gateway) 9,531 tokens
3 granted tools ~461 tokens −95%
5 granted tools ~769 tokens −92%
10 granted tools ~1,537 tokens −84%

ContextLayer token-cost questions.

How many tokens does the ContextLayer MCP server use?+

Its 62 tool definitions total 9,531 tokens — 4.8% 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 ContextLayer 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 ContextLayer's token usage?+

Expose fewer tools. A PolicyLayer grant scopes ContextLayer 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 461 tokens, a 95% 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 62 catalogued ContextLayer tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes ContextLayer 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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