Home / Token cost / Alya — The Hub for Autonomous Agents

The Alya — The Hub for Autonomous Agents MCP server costs 4,041 tokens before the first call.

Connect Alya — The Hub for Autonomous Agents and its 32 tool definitions are loaded into the model's context on every request — 2.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Alya — The Hub for Autonomous Agents MCP server's tool definitions consume 4,041 tokens — 2.1× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 32 tools · 4,041 tokens · 2.0% of 200k · 0.4% 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 2.0%
1M WINDOW 0.4%

Corpus context: Alya — The Hub for Autonomous Agents ranks #1141 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 4,041 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 126 tokens per tool.

ToolCategoryTokens% of server
alya_loss_check Read 281 7.0%
polymarket_signals Read 215 5.3%
calibrate_decision Read 212 5.2%
alya_symptom_check Read 206 5.1%
alya_seismic_forecast Read 175 4.3%
alya_drug_interactions Read 168 4.2%
alya_clone_chat Write 166 4.1%
alya_celeb_summary Read 164 4.1%
alya_gem_appraise Execute 163 4.0%
alya_gems_recent Read 158 3.9%
alya_demands_trending Read 138 3.4%
alya_app_directory Read 137 3.4%
alya_seismic_recent Read 134 3.3%
alya_iconic_clones Read 133 3.3%
polymarket_categorize Read 133 3.3%
batch_calibrate Read 132 3.3%
polymarket_top_traders Read 128 3.2%
youtube_find_opportunities Read 127 3.1%
youtube_generate_video Write 123 3.0%
alya_weather_now Read 107 2.6%
youtube_upload_video Write 95 2.4%
get_domain_accuracy Read 88 2.2%
image_gen Read 82 2.0%
web_search Read 77 1.9%
agent_registry Read 75 1.9%
alya_ask Read 73 1.8%
polymarket_edge Read 73 1.8%
youtube_get_performance Read 68 1.7%
youtube_health_check Read 59 1.5%
youtube_get_pipeline_status Read 54 1.3%
youtube_get_recommendations Read 54 1.3%
alpaca_paper_status Read 43 1.1%

Most agents use a handful of these tools. They pay for all 32.

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 (126 tokens each).

Grant scopeDefinition costReduction
All 32 tools (no gateway) 4,041 tokens
3 granted tools ~379 tokens −91%
5 granted tools ~631 tokens −84%
10 granted tools ~1,263 tokens −69%

Alya — The Hub for Autonomous Agents token-cost questions.

How many tokens does the Alya — The Hub for Autonomous Agents MCP server use?+

Its 32 tool definitions total 4,041 tokens — 2.0% 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 Alya — The Hub for Autonomous Agents 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 Alya — The Hub for Autonomous Agents's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Alya — The Hub for Autonomous Agents 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 379 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 32 catalogued Alya — The Hub for Autonomous Agents tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Alya — The Hub for Autonomous Agents 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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