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The Fdic MCP server costs 9,943 tokens before the first call.

Connect Fdic and its 29 tool definitions are loaded into the model's context on every request — 5.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Fdic MCP server's tool definitions consume 9,943 tokens — 5.2× 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 · 9,943 tokens · 5.0% 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 5.0%
1M WINDOW 1.0%

Corpus context: Fdic ranks #171 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 9,943 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 343 tokens per tool.

ToolCategoryTokens% of server
fdic_compare_bank_snapshots Write 1,004 10.1%
fdic_peer_group_analysis Execute 736 7.4%
fdic_compare_peer_health Write 529 5.3%
fdic_search_financials Read 514 5.2%
fdic_detect_risk_signals Read 512 5.1%
fdic_search_demographics Read 485 4.9%
fdic_market_share_analysis Read 461 4.6%
fdic_search_sod Read 461 4.6%
fdic_search_summary Read 455 4.6%
fdic_search_locations Read 446 4.5%
fdic_search_history Read 442 4.4%
fdic_search_institutions Read 411 4.1%
fdic_search_failures Read 408 4.1%
fdic_analyze_bank_health Read 368 3.7%
fdic_ubpr_analysis Read 289 2.9%
fdic_regional_context Read 267 2.7%
fdic_qbp_lite_data Read 225 2.3%
fdic_analyze_credit_concentration Read 219 2.2%
fdic_analyze_securities_portfolio Read 208 2.1%
fdic_franchise_footprint Read 208 2.1%
fdic_holding_company_profile Read 204 2.1%
fdic_analyze_funding_profile Read 195 2.0%
fdic_show_bank_deep_dive Read 160 1.6%
fdic_fetch Read 137 1.4%
fdic_get_institution_failure Read 135 1.4%
fetch Read 135 1.4%
fdic_get_institution Read 123 1.2%
fdic_search Read 104 1.0%
search Read 102 1.0%

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 (343 tokens each).

Grant scopeDefinition costReduction
All 29 tools (no gateway) 9,943 tokens
3 granted tools ~1,029 tokens −90%
5 granted tools ~1,714 tokens −83%
10 granted tools ~3,429 tokens −66%

Fdic token-cost questions.

How many tokens does the Fdic MCP server use?+

Its 29 tool definitions total 9,943 tokens — 5.0% 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 Fdic 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 Fdic's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Fdic 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 1,029 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 Fdic tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Fdic 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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