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The AgentHC Market Intelligence MCP server costs 1,267 tokens before the first call.

Connect AgentHC Market Intelligence and its 28 tool definitions are loaded into the model's context on every request — 0.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The AgentHC Market Intelligence MCP server's tool definitions consume 1,267 tokens — below the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 28 tools · 1,267 tokens · 0.6% of 200k · 0.1% 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 0.6%
1M WINDOW 0.1%

Corpus context: AgentHC Market Intelligence ranks #1971 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 1,267 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 45 tokens per tool.

ToolCategoryTokens% of server
get_unified_view Read 83 6.6%
get_technical_analysis Read 60 4.7%
get_market_snapshot Read 51 4.0%
get_bonds_data Read 46 3.6%
get_crypto_derivatives Read 45 3.6%
get_fed_data Read 45 3.6%
get_hedge_fund_setups Read 45 3.6%
get_macro_data Read 45 3.6%
get_credit_cycle Read 44 3.5%
get_crypto_data Read 44 3.5%
get_currency Read 44 3.5%
get_divergences Read 44 3.5%
get_positioning Read 44 3.5%
get_tail_risk Read 44 3.5%
get_vol_surface Read 44 3.5%
get_etf_flows Read 43 3.4%
get_liquidity Read 43 3.4%
get_polymarket Read 43 3.4%
get_alpha_signals Read 42 3.3%
get_options_flow Read 42 3.3%
get_sectors Read 42 3.3%
get_correlations Read 41 3.2%
get_economic_calendar Read 41 3.2%
get_smart_money Read 41 3.2%
get_valuations Read 41 3.2%
get_earnings Read 40 3.2%
get_news_sentiment Read 40 3.2%
get_regime Read 40 3.2%

Most agents use a handful of these tools. They pay for all 28.

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 (45 tokens each).

Grant scopeDefinition costReduction
All 28 tools (no gateway) 1,267 tokens
3 granted tools ~136 tokens −89%
5 granted tools ~226 tokens −82%
10 granted tools ~453 tokens −64%

AgentHC Market Intelligence token-cost questions.

How many tokens does the AgentHC Market Intelligence MCP server use?+

Its 28 tool definitions total 1,267 tokens — 0.6% 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 AgentHC Market Intelligence 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 AgentHC Market Intelligence 's token usage?+

Expose fewer tools. A PolicyLayer grant scopes AgentHC Market Intelligence 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 136 tokens, a 89% 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 28 catalogued AgentHC Market Intelligence tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes AgentHC Market Intelligence 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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