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The Housing Intel MCP server costs 9,171 tokens before the first call.

Connect Housing Intel and its 30 tool definitions are loaded into the model's context on every request — 4.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The Housing Intel MCP server's tool definitions consume 9,171 tokens — 4.8× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 30 tools · 9,171 tokens · 4.6% of 200k · 0.9% 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 4.6%
1M WINDOW 0.9%

Corpus context: Housing Intel ranks #196 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 9,171 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 306 tokens per tool.

ToolCategoryTokens% of server
polymarket_edges Destructive 1,070 11.7%
bet_research Read 967 10.5%
polymarket_kalshi_spread Read 588 6.4%
polymarket_arbitrage Read 390 4.3%
ask_pipeworx Read 359 3.9%
recent_changes Read 359 3.9%
entity_profile Read 347 3.8%
pipeworx_feedback Read 327 3.6%
case_shiller_metro_compare Read 326 3.6%
discover_tools Write 316 3.4%
compare_entities Read 315 3.4%
ai_visibility_check Read 305 3.3%
resolve_entity Write 289 3.2%
scan_dependency Read 278 3.0%
housing_rental_analysis Read 269 2.9%
scan_competitor_ai_presence Read 269 2.9%
housing_affordability_check Read 247 2.7%
housing_market_screen Read 242 2.6%
validate_claim Read 225 2.5%
housing_metro_demand Read 217 2.4%
pipeworx_trending Read 197 2.1%
housing_market_snapshot Read 190 2.1%
generate_llms_txt Write 185 2.0%
housing_mortgage_history Read 175 1.9%
housing_property_report Read 169 1.8%
remember Destructive 168 1.8%
recall Destructive 130 1.4%
housing_signal_scan Read 88 1.0%
forget Destructive 83 0.9%
housing_employment_outlook Read 81 0.9%

Most agents use a handful of these tools. They pay for all 30.

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 (306 tokens each).

Grant scopeDefinition costReduction
All 30 tools (no gateway) 9,171 tokens
3 granted tools ~917 tokens −90%
5 granted tools ~1,529 tokens −83%
10 granted tools ~3,057 tokens −67%

Housing Intel token-cost questions.

How many tokens does the Housing Intel MCP server use?+

Its 30 tool definitions total 9,171 tokens — 4.6% 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 Housing Intel 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 Housing Intel's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Housing Intel 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 917 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 30 catalogued Housing Intel tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Housing Intel 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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