Home / Token cost / Reel25 — Video Analytics for TikTok, Instagram & YouTube

The Reel25 — Video Analytics for TikTok, Instagram & YouTube MCP server costs 2,035 tokens before the first call.

Connect Reel25 — Video Analytics for TikTok, Instagram & YouTube and its 26 tool definitions are loaded into the model's context on every request — 1.0% of a 200k window spent before your agent does anything.

QUICK ANSWER The Reel25 — Video Analytics for TikTok, Instagram & YouTube MCP server's tool definitions consume 2,035 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 26 tools · 2,035 tokens · 1.0% 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 1.0%
1M WINDOW 0.2%

Corpus context: Reel25 — Video Analytics for TikTok, Instagram & YouTube ranks #1558 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 2,035 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 78 tokens per tool.

ToolCategoryTokens% of server
search_content Read 196 9.6%
list_videos Read 143 7.0%
analyze_video Read 102 5.0%
track_account Read 100 4.9%
add_videos_to_folder Write 97 4.8%
add_accounts_to_folder Write 96 4.7%
get_video_history Read 88 4.3%
get_account_videos Read 85 4.2%
bulk_track_videos Read 83 4.1%
growth_trends Read 79 3.9%
track_video Read 75 3.7%
get_radar_results Read 68 3.3%
top_videos Read 68 3.3%
get_video Read 67 3.3%
get_analysis Read 66 3.2%
create_folder Write 66 3.2%
get_account_metrics Read 65 3.2%
folder_analytics Read 64 3.1%
untrack_video Read 64 3.1%
remove_account Destructive 63 3.1%
radar_history Read 63 3.1%
get_account Read 62 3.0%
get_workspace Read 47 2.3%
get_credits Read 43 2.1%
list_accounts Read 43 2.1%
list_folders Read 42 2.1%

Most agents use a handful of these tools. They pay for all 26.

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 (78 tokens each).

Grant scopeDefinition costReduction
All 26 tools (no gateway) 2,035 tokens
3 granted tools ~235 tokens −88%
5 granted tools ~391 tokens −81%
10 granted tools ~783 tokens −62%

Reel25 — Video Analytics for TikTok, Instagram & YouTube token-cost questions.

How many tokens does the Reel25 — Video Analytics for TikTok, Instagram & YouTube MCP server use?+

Its 26 tool definitions total 2,035 tokens — 1.0% 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 Reel25 — Video Analytics for TikTok, Instagram & YouTube 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 Reel25 — Video Analytics for TikTok, Instagram & YouTube's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Reel25 — Video Analytics for TikTok, Instagram & YouTube 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 235 tokens, a 88% 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 26 catalogued Reel25 — Video Analytics for TikTok, Instagram & YouTube tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Reel25 — Video Analytics for TikTok, Instagram & YouTube 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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