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The Forex-GPT MCP Server MCP server costs 6,971 tokens before the first call.

Connect Forex-GPT MCP Server and its 45 tool definitions are loaded into the model's context on every request — 3.5% of a 200k window spent before your agent does anything.

QUICK ANSWER The Forex-GPT MCP Server MCP server's tool definitions consume 6,971 tokens — 3.7× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 45 tools · 6,971 tokens · 3.5% of 200k · 0.7% 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 3.5%
1M WINDOW 0.7%

Corpus context: Forex-GPT MCP Server ranks #904 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 6,971 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 155 tokens per tool.

ToolCategoryTokens% of server
get_instrument_specs Read 407 5.8%
trade_stop_order Execute 388 5.6%
is_market_open Read 352 5.0%
trade_limit_order Execute 351 5.0%
get_market_hours Read 321 4.6%
trade_market_order Read 317 4.5%
replace_pending_order Write 290 4.2%
scan_market Read 280 4.0%
analyze_watchlist Read 256 3.7%
trade_modify_trade Write 233 3.3%
analyze_asset Read 209 3.0%
analyze_timeframes Read 209 3.0%
get_live_heatmap Read 201 2.9%
get_account_history Read 190 2.7%
get_chart_data Read 180 2.6%
chart_chat_proxy Read 178 2.6%
get_spreads Read 160 2.3%
refresh_instrument_data Read 158 2.3%
health Read 150 2.2%
economic_events Execute 138 2.0%
search Read 119 1.7%
get_instrument_cache_status Read 116 1.7%
get_blog_articles Read 113 1.6%
get_order_history Read 113 1.6%
fetch Read 110 1.6%
get_sentiment_stream_url Read 108 1.5%
list_assets Read 99 1.4%
get_token_balances Read 97 1.4%
save_oanda_credentials Write 89 1.3%
get_price_stream_url Read 87 1.2%
add_to_watchlist Write 87 1.2%
cancel_pending_order Destructive 81 1.2%
close_position Write 79 1.1%
get_trade_details Read 78 1.1%
get_market_categories Read 76 1.1%
remove_from_watchlist Destructive 73 1.0%
close_trade Write 67 1.0%
delete_oanda_credentials Destructive 63 0.9%
get_open_positions Read 60 0.9%
get_watchlist Read 60 0.9%
get_pending_orders Read 57 0.8%
help_tutorial Read 50 0.7%
get_server_time Read 47 0.7%
get_trading_account Read 40 0.6%
get_open_trades Read 34 0.5%

Most agents use a handful of these tools. They pay for all 45.

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 (155 tokens each).

Grant scopeDefinition costReduction
All 45 tools (no gateway) 6,971 tokens
3 granted tools ~465 tokens −93%
5 granted tools ~775 tokens −89%
10 granted tools ~1,549 tokens −78%

Forex-GPT MCP Server token-cost questions.

How many tokens does the Forex-GPT MCP Server MCP server use?+

Its 45 tool definitions total 6,971 tokens — 3.5% 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 Forex-GPT MCP 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 Forex-GPT MCP Server's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Forex-GPT MCP 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 465 tokens, a 93% 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 45 catalogued Forex-GPT MCP Server tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Forex-GPT MCP 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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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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