Home / Token cost / Pearlog

The Pearlog MCP server costs 1,313 tokens before the first call.

Every request your agent makes carries every tool definition this server exposes — context your code, documents and conversation can't use, mostly for tools the agent never calls. You don't need them all in the window, and you don't have to pay for them.

QUICK ANSWER The Pearlog MCP server's 10 tool definitions consume 1,313 tokens — 0.7% of a 200k context window, and below the median MCP server (2,069 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS tiktoken o200k_base · rank #2086 of 3,354 measured servers · refreshed every build Method →

What that costs 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 0.7%
1M WINDOW 0.1%

Corpus context: Pearlog ranks #2086 of 3,354 measured MCP servers by definition cost. The median is 2,069 tokens, p90 is 11,359, and the heaviest (SmartBear MCP) is 137,725 — 69% of a 200k window on its own. New to this? See MCP token cost and context window in the glossary.

Where the 1,313 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 131 tokens per tool.

ToolCategoryTokens% of server
create_ticket Write 282 21.5%
patch_ticket Write 267 20.3%
update_ticket Write 260 19.8%
list_tickets Read 164 12.5%
get_status_labels Read 70 5.3%
list_users Read 62 4.7%
move_ticket Write 62 4.7%
list_projects Read 61 4.6%
get_ticket Read 43 3.3%
delete_ticket Destructive 42 3.2%

Your agent uses a handful of these tools. It pays for all 10.

You don't need all 10 of those definitions in the window. PolicyLayer is an MCP gateway that sits in front of Pearlog: only the tools you grant are exposed to the agent, the rest never load. A smaller window means a sharper agent — less noise when it picks a tool — and every request costs less:

Grant scopeDefinition costReduction
All 10 tools (no gateway) 1,313 tokens
3 granted tools ~394 tokens −70%
5 granted tools ~657 tokens −50%

The risk dividend: 1 of these 10 tools are critical-risk (destructive or financial) and cost 42 tokens (3% of the definition load). Block them — the recommended starter policy — and you reclaim that context before tuning anything else.

  1. Create a free account and register Pearlog — nothing to install.
  2. Grant only the tools you use — ungranted definitions never enter the context window.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
CUT PEARLOG TOKEN COST →

Instant setup, no code required.

Pearlog token-cost questions.

How many tokens does the Pearlog MCP server use?+

Its 10 tool definitions total 1,313 tokens — 0.7% 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 Pearlog 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 Pearlog's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Pearlog 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 394 tokens, a 70% 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 06-07-2026 from the PolicyLayer scan database over all 10 catalogued Pearlog tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Pearlog to the tools you actually allow. Ungranted definitions never load, and every call that does run is checked against policy first.

Instant setup, no code required.

43,000+ MCP servers and 220,000+ tools scanned and risk-classified.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.