// MCP TOKEN COST

The AiPayGen MCP server costs 7,391 tokens before the first call.

Connect AiPayGen and its 106 tool definitions are loaded into the model's context on every request — 3.7% of a 200k window spent before your agent does anything.

QUICK ANSWER The AiPayGen MCP server's tool definitions consume 7,391 tokens — 3.9× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 106 tools · 7,391 tokens · 3.7% of 200k · 0.7% of 1M Method →

// CONTEXT WINDOW SHARE

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 3.7%

1M WINDOW 0.7%

Corpus context: AiPayGen ranks #807 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.

// PER-TOOL BREAKDOWN

Where the 7,391 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 70 tokens per tool.

Tool	Category	Tokens	% of server
post_to_marketplace	Write	223	3.0%
chain_operations	Read	178	2.4%
pipeline	Read	172	2.3%
batch	Execute	158	2.1%
browse_catalog	Read	145	2.0%
think	Read	137	1.9%
register_my_agent	Write	123	1.7%
invoke_catalog_api	Execute	117	1.6%
memory_store	Read	113	1.5%
list_marketplace	Read	108	1.5%
submit_agent_task	Write	108	1.5%
email	Read	97	1.3%
create_agent	Write	97	1.3%
pitch	Read	90	1.2%
workflow	Read	90	1.2%
tag	Read	84	1.1%
social	Read	83	1.1%
add_to_knowledge_base	Write	83	1.1%
create_skill	Write	82	1.1%
score	Read	81	1.1%
schedule_agent	Write	80	1.1%
send_agent_message	Write	80	1.1%
run_python_code	Execute	78	1.1%
decide	Read	78	1.1%
diagram	Read	78	1.1%
extract	Read	77	1.0%
review_code	Read	77	1.0%
rag	Read	76	1.0%
search_skills	Read	76	1.0%
explain	Read	74	1.0%
questions	Read	74	1.0%
name_generator	Read	73	1.0%
rewrite	Read	73	1.0%
sql	Read	71	1.0%
convert_code	Write	71	1.0%
plan	Write	71	1.0%
get_holidays	Read	70	0.9%
mock	Read	70	0.9%
scrape_tweets	Read	70	0.9%
compare	Read	69	0.9%
outline	Read	69	0.9%
absorb_skill	Read	68	0.9%
headline	Read	68	0.9%
regex	Read	68	0.9%
scrape_google_maps	Read	68	0.9%
scrape_website	Read	67	0.9%
scrape_youtube	Read	67	0.9%
chat	Write	67	0.9%
scrape_tiktok	Read	66	0.9%
read_agent_inbox	Read	65	0.9%
scrape_instagram	Read	65	0.9%
vision	Read	65	0.9%
parse_csv	Execute	64	0.9%
changelog	Read	64	0.9%
execute_skill	Execute	63	0.9%
browse_agent_tasks	Read	62	0.8%
analyze	Read	61	0.8%
json_schema	Read	61	0.8%
test_cases	Read	61	0.8%
generate_docs	Write	61	0.8%
write	Write	61	0.8%
memory_recall	Read	60	0.8%
web_search	Read	60	0.8%
classify	Read	59	0.8%
diff	Read	59	0.8%
enrich_entity	Read	59	0.8%
generate_api_spec	Write	59	0.8%
run_agent	Execute	58	0.8%
summarize	Read	58	0.8%
transform	Execute	57	0.8%
get_exchange_rates	Read	57	0.8%
memory_find	Read	57	0.8%
timeline	Read	57	0.8%
debate	Read	56	0.8%
code	Read	55	0.7%
keywords	Read	55	0.7%
proofread	Read	55	0.7%
generate_api_key	Write	55	0.7%
fact	Read	54	0.7%
get_crypto_prices	Read	54	0.7%
qa	Read	54	0.7%
search_knowledge_base	Read	53	0.7%
list_skills	Read	51	0.7%
privacy_check	Read	50	0.7%
translate	Read	48	0.6%
get_weather	Read	47	0.6%
memory_keys	Read	47	0.6%
cron_expression	Read	46	0.6%
get_catalog_api	Read	46	0.6%
generate_uuid	Write	46	0.6%
action	Read	45	0.6%
ask	Read	44	0.6%
check_api_key_balance	Read	44	0.6%
research	Read	43	0.6%
sentiment	Read	43	0.6%
get_current_time	Read	41	0.6%
check_balance	Read	39	0.5%
get_agent_runs	Read	38	0.5%
list_my_agents	Read	38	0.5%
delete_agent	Destructive	37	0.5%
get_trending_knowledge	Read	35	0.5%
pause_agent	Read	35	0.5%
list_registered_agents	Read	32	0.4%
list_models	Read	31	0.4%
get_joke	Read	29	0.4%
get_quote	Read	29	0.4%

// SCOPED GRANT

Most agents use a handful of these tools. They pay for all 106.

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 (70 tokens each).

Grant scope	Definition cost	Reduction
All 106 tools (no gateway)	7,391 tokens	—
3 granted tools	~209 tokens	−97%
5 granted tools	~349 tokens	−95%
10 granted tools	~697 tokens	−91%

Model your own stack in the token-cost calculator, or see the AiPayGen policy for what a sensible grant looks like.

//FAQ

AiPayGen token-cost questions.

How many tokens does the AiPayGen MCP server use?+

Its 106 tool definitions total 7,391 tokens — 3.7% 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 AiPayGen 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 AiPayGen's token usage?+

Expose fewer tools. A PolicyLayer grant scopes AiPayGen 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 209 tokens, a 97% 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.

// METHOD & REVIEW

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 106 catalogued AiPayGen tools. Counts refresh with every site build.