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The Avalanche AVAX MCP server costs 4,415 tokens before the first call.

Connect Avalanche AVAX and its 44 tool definitions are loaded into the model's context on every request — 2.2% of a 200k window spent before your agent does anything.

QUICK ANSWER The Avalanche AVAX MCP MCP server's tool definitions consume 4,415 tokens — 2.3× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 44 tools · 4,415 tokens · 2.2% 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 2.2%
1M WINDOW 0.4%

Corpus context: Avalanche AVAX ranks #1093 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 4,415 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 100 tokens per tool.

ToolCategoryTokens% of server
github_search_code Read 251 5.7%
acp_list Read 171 3.9%
github_get_file Read 166 3.8%
platform_get_validators_at Read 159 3.6%
rpc_lookup_method Read 142 3.2%
platform_get_utxos Read 141 3.2%
cli_lookup_command Read 129 2.9%
blockchain_lookup_transaction Read 125 2.8%
acp_lookup Read 124 2.8%
blockchain_lookup_validator Read 119 2.7%
docs_search Read 117 2.7%
info_peers Read 117 2.7%
platform_get_pending_validators Read 116 2.6%
info_get_blockchain_id Read 115 2.6%
platform_get_block Read 110 2.5%
platform_get_tx Read 110 2.5%
avalanche_docs_search Read 109 2.5%
platform_get_current_validators Read 109 2.5%
platform_get_block_by_height Read 108 2.4%
platform_get_balance Read 103 2.3%
blockchain_lookup_address Read 102 2.3%
info_is_bootstrapped Read 99 2.2%
blockchain_get_contract_info Read 98 2.2%
blockchain_get_native_balance Read 94 2.1%
platform_get_staking_asset_id Read 92 2.1%
platform_get_min_stake Read 90 2.0%
platform_get_current_supply Read 87 2.0%
platform_get_total_stake Read 86 1.9%
platform_get_subnets Read 85 1.9%
blockchain_lookup_subnet Read 83 1.9%
platform_get_tx_status Read 83 1.9%
blockchain_lookup_chain Read 76 1.7%
info_get_node_version Read 72 1.6%
info_get_tx_fee Read 71 1.6%
info_acps Read 69 1.6%
info_get_network_name Read 67 1.5%
info_get_network_id Read 66 1.5%
avalanche_docs_fetch Read 64 1.4%
platform_get_blockchains Read 61 1.4%
platform_get_height Read 57 1.3%
docs_fetch Read 56 1.3%
avalanche_docs_list_sections Read 42 1.0%
github_list_repositories Read 41 0.9%
docs_list_sections Read 33 0.7%

Most agents use a handful of these tools. They pay for all 44.

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 (100 tokens each).

Grant scopeDefinition costReduction
All 44 tools (no gateway) 4,415 tokens
3 granted tools ~301 tokens −93%
5 granted tools ~502 tokens −89%
10 granted tools ~1,003 tokens −77%

Avalanche AVAX MCP token-cost questions.

How many tokens does the Avalanche AVAX MCP server use?+

Its 44 tool definitions total 4,415 tokens — 2.2% 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 Avalanche AVAX MCP 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 Avalanche AVAX MCP's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Avalanche AVAX MCP 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 301 tokens, a 93% 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 44 catalogued Avalanche AVAX MCP tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Avalanche AVAX MCP 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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