Home / Token cost / FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT

The FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT MCP server costs 2,680 tokens before the first call.

Connect FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT and its 13 tool definitions are loaded into the model's context on every request — 1.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT MCP server's tool definitions consume 2,680 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 13 tools · 2,680 tokens · 1.3% 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 1.3%
1M WINDOW 0.3%

Corpus context: FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT ranks #1372 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 2,680 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 206 tokens per tool.

ToolCategoryTokens% of server
jobs_search Read 488 18.2%
tracker_update Write 351 13.1%
tracker_add Write 250 9.3%
job_alert_subscribe Read 237 8.8%
job_alert_list Read 215 8.0%
reminder_set Write 189 7.1%
tracker_list Read 185 6.9%
job_alert_unsubscribe Read 171 6.4%
tracker_update_status Write 160 6.0%
jobs_details Read 145 5.4%
reminder_list Read 111 4.1%
tracker_remove Destructive 90 3.4%
reminder_delete Destructive 88 3.3%

Most agents use a handful of these tools. They pay for all 13.

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 (206 tokens each).

Grant scopeDefinition costReduction
All 13 tools (no gateway) 2,680 tokens
3 granted tools ~618 tokens −77%
5 granted tools ~1,031 tokens −62%
10 granted tools ~2,062 tokens −23%

FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT token-cost questions.

How many tokens does the FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT MCP server use?+

Its 13 tool definitions total 2,680 tokens — 1.3% 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 FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT 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 FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT's token usage?+

Expose fewer tools. A PolicyLayer grant scopes FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT 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 618 tokens, a 77% 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 13 catalogued FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT 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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