Home / Token cost / aaaa-nexus — Formally Verified AI Safety APIs

The aaaa-nexus — Formally Verified AI Safety APIs MCP server costs 1,645 tokens before the first call.

Connect aaaa-nexus — Formally Verified AI Safety APIs and its 27 tool definitions are loaded into the model's context on every request — 0.8% of a 200k window spent before your agent does anything.

QUICK ANSWER The aaaa-nexus — Formally Verified AI Safety APIs MCP server's tool definitions consume 1,645 tokens — around the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 27 tools · 1,645 tokens · 0.8% of 200k · 0.2% 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 0.8%
1M WINDOW 0.2%

Corpus context: aaaa-nexus — Formally Verified AI Safety APIs ranks #1734 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 1,645 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 61 tokens per tool.

ToolCategoryTokens% of server
ratchet_register Write 69 4.2%
vanguard_escrow_lock_and_verify Write 68 4.1%
aegis_router_epistemic_bound Read 67 4.1%
aegis_mcp_proxy_execute Execute 66 4.0%
vanguard_continuous_redteam Read 66 4.0%
vanguard_mev_route_intent Read 66 4.0%
uep_autopoiesis_plan Write 66 4.0%
vanguard_wallet_govern_session Read 64 3.9%
uep_aha_detect Read 63 3.8%
uep_preflight Read 63 3.8%
sys_trust_gate Read 62 3.8%
uep_synthesis_guard Read 62 3.8%
uep_trace_certify Read 62 3.8%
text_summarize Read 61 3.7%
uep_context Read 61 3.7%
lineage_record Read 59 3.6%
spending_authorize Read 59 3.6%
sys_constants Read 59 3.6%
rag_augment Read 58 3.5%
rng_quantum Read 58 3.5%
authorize_action Read 57 3.5%
federation_mint Read 57 3.5%
sys_lint_gate Read 57 3.5%
contract_verify Read 56 3.4%
threat_score Read 56 3.4%
hallucination_oracle Read 55 3.3%
identity_verify Read 48 2.9%

Most agents use a handful of these tools. They pay for all 27.

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 (61 tokens each).

Grant scopeDefinition costReduction
All 27 tools (no gateway) 1,645 tokens
3 granted tools ~183 tokens −89%
5 granted tools ~305 tokens −81%
10 granted tools ~609 tokens −63%

aaaa-nexus — Formally Verified AI Safety APIs token-cost questions.

How many tokens does the aaaa-nexus — Formally Verified AI Safety APIs MCP server use?+

Its 27 tool definitions total 1,645 tokens — 0.8% 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 aaaa-nexus — Formally Verified AI Safety APIs 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 aaaa-nexus — Formally Verified AI Safety APIs's token usage?+

Expose fewer tools. A PolicyLayer grant scopes aaaa-nexus — Formally Verified AI Safety APIs 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 183 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 27 catalogued aaaa-nexus — Formally Verified AI Safety APIs tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes aaaa-nexus — Formally Verified AI Safety APIs to the tools you actually allow. Ungranted definitions never load, and every call that does run is checked against policy first.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.