Home / Token cost / Swarm Tips — Aggregated AI Agent Activities

The Swarm Tips — Aggregated AI Agent Activities MCP server costs 7,913 tokens before the first call.

Connect Swarm Tips — Aggregated AI Agent Activities and its 33 tool definitions are loaded into the model's context on every request — 4.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Swarm Tips — Aggregated AI Agent Activities MCP server's tool definitions consume 7,913 tokens — 4.2× 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 · 7,913 tokens · 4.0% of 200k · 0.8% 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 4.0%
1M WINDOW 0.8%

Corpus context: Swarm Tips — Aggregated AI Agent Activities ranks #340 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 7,913 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 240 tokens per tool.

ToolCategoryTokens% of server
shillbot_get_attestation Destructive 534 6.7%
agent_trust_score Read 403 5.1%
search_mcp_servers Read 393 5.0%
list_earning_opportunities Read 375 4.7%
shillbot_submit_tx Write 371 4.7%
shillbot_complete_task Write 328 4.1%
discover_opportunities Read 322 4.1%
list_spending_opportunities Read 310 3.9%
shillbot_reject_task Write 297 3.8%
shillbot_approve_task Write 291 3.7%
agent_profile Read 279 3.5%
game_find_match Read 277 3.5%
shillbot_submit_work Write 275 3.5%
shillbot_list_available_tasks Read 267 3.4%
generate_video Write 266 3.4%
shillbot_verify_task Read 252 3.2%
shillbot_list_pending_approval Read 241 3.0%
shillbot_finalize_task Financial 237 3.0%
shillbot_claim_task Read 229 2.9%
game_submit_tx Write 222 2.8%
register_wallet Write 212 2.7%
shillbot_check_earnings Read 187 2.4%
shillbot_get_task_details Read 184 2.3%
game_get_leaderboard Read 177 2.2%
list_extensions Read 159 2.0%
query_agent_credit_web_score Read 158 2.0%
game_commit_guess Write 133 1.7%
game_send_message Write 122 1.5%
game_reveal_guess Read 113 1.4%
check_video_status Read 97 1.2%
game_get_messages Read 88 1.1%
game_check_match Read 65 0.8%
game_get_result Read 49 0.6%

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 (240 tokens each).

Grant scopeDefinition costReduction
All 33 tools (no gateway) 7,913 tokens
3 granted tools ~719 tokens −91%
5 granted tools ~1,199 tokens −85%
10 granted tools ~2,398 tokens −70%

Swarm Tips — Aggregated AI Agent Activities token-cost questions.

How many tokens does the Swarm Tips — Aggregated AI Agent Activities MCP server use?+

Its 33 tool definitions total 7,913 tokens — 4.0% 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 Swarm Tips — Aggregated AI Agent Activities 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 Swarm Tips — Aggregated AI Agent Activities's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Swarm Tips — Aggregated AI Agent Activities 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 719 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 Swarm Tips — Aggregated AI Agent Activities tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Swarm Tips — Aggregated AI Agent Activities 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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