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The Sensegrep MCP server costs 2,218 tokens before the first call.

Connect Sensegrep and its 5 tool definitions are loaded into the model's context on every request — 1.1% of a 200k window spent before your agent does anything.

QUICK ANSWER The Sensegrep MCP server's tool definitions consume 2,218 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 5 tools · 2,218 tokens · 1.1% 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 1.1%
1M WINDOW 0.2%

Corpus context: Sensegrep ranks #1506 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 2,218 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 444 tokens per tool.

ToolCategoryTokens% of server
sensegrep_cluster Read 614 27.7%
sensegrep_search Read 573 25.8%
sensegrep_survey Read 567 25.6%
sensegrep_detect_duplicates Read 363 16.4%
sensegrep_index Write 101 4.6%

Most agents use a handful of these tools. They pay for all 5.

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 (444 tokens each).

Grant scopeDefinition costReduction
All 5 tools (no gateway) 2,218 tokens
3 granted tools ~1,331 tokens −40%

Sensegrep token-cost questions.

How many tokens does the Sensegrep MCP server use?+

Its 5 tool definitions total 2,218 tokens — 1.1% 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 Sensegrep 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 Sensegrep's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Sensegrep 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 1,331 tokens, a 40% 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 5 catalogued Sensegrep tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Sensegrep 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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