Home / Token cost / Push Realm

The Push Realm MCP server costs 7,214 tokens before the first call.

Connect Push Realm and its 31 tool definitions are loaded into the model's context on every request — 3.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The Push Realm MCP server's tool definitions consume 7,214 tokens — 3.8× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 31 tools · 7,214 tokens · 3.6% of 200k · 0.7% 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 3.6%
1M WINDOW 0.7%

Corpus context: Push Realm ranks #882 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 7,214 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 233 tokens per tool.

ToolCategoryTokens% of server
submit_learning Write 1,302 18.0%
suggest_edit Write 755 10.5%
submit_open_issue Write 745 10.3%
search_learnings Read 731 10.1%
compress_learnings Write 399 5.5%
resolve_open_issue Write 384 5.3%
link_learnings Write 288 4.0%
get_compression_candidates Read 237 3.3%
absorb_addendums Execute 211 2.9%
add_addendum Write 210 2.9%
search_open_issues Read 199 2.8%
confirm_learning Destructive 181 2.5%
request_delete_learning Destructive 141 2.0%
report_learning Write 135 1.9%
unlink_learnings Destructive 131 1.8%
request_delete_addendum Destructive 121 1.7%
record_agent_usage Read 117 1.6%
reject_learning Write 117 1.6%
confirm_resolve_open_issue Write 116 1.6%
get_learning_relations Read 78 1.1%
confirm_edit Write 70 1.0%
confirm_open_issue Write 69 1.0%
confirm_compression Write 62 0.9%
confirm_delete_addendum Destructive 56 0.8%
reject_compression Write 55 0.8%
reject_open_issue Write 55 0.8%
confirm_delete_learning Destructive 54 0.7%
reject_edit Write 54 0.7%
reject_resolve_open_issue Write 49 0.7%
reject_delete_addendum Write 47 0.7%
reject_delete_learning Write 45 0.6%

Most agents use a handful of these tools. They pay for all 31.

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 (233 tokens each).

Grant scopeDefinition costReduction
All 31 tools (no gateway) 7,214 tokens
3 granted tools ~698 tokens −90%
5 granted tools ~1,164 tokens −84%
10 granted tools ~2,327 tokens −68%

Push Realm token-cost questions.

How many tokens does the Push Realm MCP server use?+

Its 31 tool definitions total 7,214 tokens — 3.6% 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 Push Realm 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 Push Realm's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Push Realm 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 698 tokens, a 90% 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 31 catalogued Push Realm tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Push Realm to the tools you actually allow. Ungranted definitions never load, and every call that does run is checked against policy first.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.