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The Terminalfeed MCP server costs 5,260 tokens before the first call.

Connect Terminalfeed and its 35 tool definitions are loaded into the model's context on every request — 2.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The Terminalfeed MCP server's tool definitions consume 5,260 tokens — 2.8× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 35 tools · 5,260 tokens · 2.6% of 200k · 0.5% 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 2.6%
1M WINDOW 0.5%

Corpus context: Terminalfeed ranks #1006 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 5,260 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 150 tokens per tool.

ToolCategoryTokens% of server
tf_climate_weather_alerts Read 246 4.7%
tf_premium_regime Read 241 4.6%
tf_premium_crypto_deep Read 225 4.3%
tf_premium_exchange_flows Read 220 4.2%
tf_premium_anomalies Read 219 4.2%
tf_harnesses Write 217 4.1%
tf_premium_briefing Read 214 4.1%
tf_premium_agent_context Execute 208 4.0%
tf_premium_world_deltas Read 204 3.9%
tf_climate_earthquakes Read 203 3.9%
tf_premium_macro Read 194 3.7%
tf_premium_sentiment Read 188 3.6%
tf_premium_feed_reliability Read 180 3.4%
tf_premium_feed_reliability_history Read 176 3.3%
tf_premium_whales Read 173 3.3%
tf_preview_regime Read 170 3.2%
tf_premium_correlation_matrix Read 167 3.2%
tf_premium_stablecoin_flows Read 163 3.1%
tf_payment_confirm Read 139 2.6%
tf_premium_github_velocity Read 137 2.6%
tf_premium_defi_tvl Read 136 2.6%
tf_payment_buy_credits Read 135 2.6%
tf_solana_network Read 110 2.1%
tf_forex Read 102 1.9%
tf_hf_trending Read 99 1.9%
tf_payment_history Read 91 1.7%
tf_briefing Read 88 1.7%
tf_service_status Read 84 1.6%
tf_economic_data Read 81 1.5%
tf_fear_greed Read 81 1.5%
tf_btc_price Read 79 1.5%
tf_crypto_movers Read 77 1.5%
tf_earthquakes Read 75 1.4%
tf_predictions Read 75 1.4%
tf_payment_balance Read 63 1.2%

Most agents use a handful of these tools. They pay for all 35.

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 (150 tokens each).

Grant scopeDefinition costReduction
All 35 tools (no gateway) 5,260 tokens
3 granted tools ~451 tokens −91%
5 granted tools ~751 tokens −86%
10 granted tools ~1,503 tokens −71%

Terminalfeed token-cost questions.

How many tokens does the Terminalfeed MCP server use?+

Its 35 tool definitions total 5,260 tokens — 2.6% 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 Terminalfeed 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 Terminalfeed's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Terminalfeed 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 451 tokens, a 91% 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 35 catalogued Terminalfeed tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Terminalfeed 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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