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The Senado Br MCP server costs 3,833 tokens before the first call.

Connect Senado Br and its 33 tool definitions are loaded into the model's context on every request — 1.9% of a 200k window spent before your agent does anything.

QUICK ANSWER The Senado Br MCP server's tool definitions consume 3,833 tokens — 2.0× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 33 tools · 3,833 tokens · 1.9% 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 1.9%
1M WINDOW 0.4%

Corpus context: Senado Br ranks #1175 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 3,833 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 116 tokens per tool.

ToolCategoryTokens% of server
senado_buscar_materias Read 209 5.5%
senado_ecidadania_sugerir_tema_enquete Read 192 5.0%
senado_ecidadania_listar_ideias Read 186 4.9%
senado_listar_senadores Read 175 4.6%
senado_listar_votacoes Read 175 4.6%
senado_votacoes_senador Read 167 4.4%
senado_ecidadania_consultas_polarizadas Read 158 4.1%
senado_ecidadania_consultas_consensuais Read 154 4.0%
senado_reunioes_comissao Read 143 3.7%
senado_agenda_plenario Read 141 3.7%
senado_ecidadania_listar_consultas Read 138 3.6%
senado_ecidadania_listar_eventos Read 135 3.5%
senado_listar_comissoes Read 128 3.3%
senado_agenda_comissoes Read 111 2.9%
senado_ecidadania_ideias_populares Read 109 2.8%
senado_ecidadania_eventos_populares Read 106 2.8%
senado_votacoes_recentes Read 100 2.6%
senado_buscar_senador_por_nome Read 95 2.5%
senado_obter_senador Read 95 2.5%
senado_ecidadania_obter_ideia Read 93 2.4%
senado_obter_comissao Read 91 2.4%
senado_obter_materia Read 90 2.3%
senado_textos_materia Read 89 2.3%
senado_membros_comissao Read 88 2.3%
senado_obter_votacao Read 88 2.3%
senado_tramitacao_materia Read 88 2.3%
senado_votos_materia Read 87 2.3%
senado_ecidadania_obter_evento Read 85 2.2%
senado_ecidadania_obter_consulta Read 84 2.2%
senado_tipos_materia Read 64 1.7%
senado_legislatura_atual Read 60 1.6%
senado_partidos Read 57 1.5%
senado_ufs Read 52 1.4%

Most agents use a handful of these tools. They pay for all 33.

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 (116 tokens each).

Grant scopeDefinition costReduction
All 33 tools (no gateway) 3,833 tokens
3 granted tools ~348 tokens −91%
5 granted tools ~581 tokens −85%
10 granted tools ~1,162 tokens −70%

Senado Br token-cost questions.

How many tokens does the Senado Br MCP server use?+

Its 33 tool definitions total 3,833 tokens — 1.9% 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 Senado Br 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 Senado Br's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Senado Br 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 348 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 33 catalogued Senado Br tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Senado Br 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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