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The Pylon Server MCP server costs 3,403 tokens before the first call.

Connect Pylon Server and its 29 tool definitions are loaded into the model's context on every request — 1.7% of a 200k window spent before your agent does anything.

QUICK ANSWER The Pylon Server MCP server's tool definitions consume 3,403 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 29 tools · 3,403 tokens · 1.7% 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 1.7%
1M WINDOW 0.3%

Corpus context: Pylon Server ranks #1244 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 3,403 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 117 tokens per tool.

ToolCategoryTokens% of server
pylon_update_issue Write 243 7.1%
pylon_create_issue Write 234 6.9%
pylon_create_ticket_form Write 213 6.3%
pylon_create_webhook Write 182 5.3%
pylon_create_knowledge_base_article Write 174 5.1%
pylon_create_team Write 174 5.1%
pylon_get_issues Read 166 4.9%
pylon_snooze_issue Write 159 4.7%
pylon_search_issues Read 157 4.6%
pylon_create_issue_message Write 140 4.1%
pylon_create_contact Write 132 3.9%
pylon_create_tag Write 126 3.7%
pylon_get_contacts Read 119 3.5%
pylon_search_contacts Read 112 3.3%
pylon_get_knowledge_base_articles Read 95 2.8%
pylon_get_issue Read 94 2.8%
pylon_search_users Read 87 2.6%
pylon_get_issue_messages Read 85 2.5%
pylon_get_account Read 83 2.4%
pylon_delete_webhook Destructive 81 2.4%
pylon_get_team Read 81 2.4%
pylon_get_tags Read 66 1.9%
pylon_get_teams Read 64 1.9%
pylon_get_knowledge_bases Read 61 1.8%
pylon_get_me Read 58 1.7%
pylon_get_webhooks Read 58 1.7%
pylon_get_ticket_forms Read 56 1.6%
pylon_get_accounts Read 54 1.6%
pylon_get_users Read 49 1.4%

Most agents use a handful of these tools. They pay for all 29.

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 (117 tokens each).

Grant scopeDefinition costReduction
All 29 tools (no gateway) 3,403 tokens
3 granted tools ~352 tokens −90%
5 granted tools ~587 tokens −83%
10 granted tools ~1,173 tokens −66%

Pylon Server token-cost questions.

How many tokens does the Pylon Server MCP server use?+

Its 29 tool definitions total 3,403 tokens — 1.7% 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 Pylon 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 Pylon Server's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Pylon 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 352 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 29 catalogued Pylon Server tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Pylon 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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