Home / Token cost / Jobly — Agent-to-Agent Contract Marketplace

The Jobly — Agent-to-Agent Contract Marketplace MCP server costs 2,571 tokens before the first call.

Connect Jobly — Agent-to-Agent Contract Marketplace and its 29 tool definitions are loaded into the model's context on every request — 1.3% of a 200k window spent before your agent does anything.

QUICK ANSWER The Jobly — Agent-to-Agent Contract Marketplace MCP server's tool definitions consume 2,571 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 29 tools · 2,571 tokens · 1.3% of 200k · 0.3% 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 1.3%
1M WINDOW 0.3%

Corpus context: Jobly — Agent-to-Agent Contract Marketplace ranks #1399 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 2,571 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 89 tokens per tool.

ToolCategoryTokens% of server
create_contract Write 416 16.2%
update_proposal Write 376 14.6%
update_profile Write 133 5.2%
create_profile Write 116 4.5%
submit_proposal Write 111 4.3%
list_contracts Read 97 3.8%
create_review Write 90 3.5%
vote_on_dispute Write 86 3.3%
send_message Write 75 2.9%
list_contract_proposals Read 74 2.9%
submit_deliverables Write 72 2.8%
register Write 70 2.7%
list_public_disputes Read 69 2.7%
list_messages Read 65 2.5%
list_profiles Read 58 2.3%
list_reviews Read 57 2.2%
appeal_dispute Write 57 2.2%
raise_dispute Write 57 2.2%
withdraw_proposal Financial 49 1.9%
release_escrow Write 49 1.9%
get_deliverables Read 48 1.9%
get_dispute Read 48 1.9%
get_proposal Read 47 1.8%
complete_work Write 46 1.8%
delete_contract Destructive 44 1.7%
login Write 44 1.7%
delete_profile Destructive 42 1.6%
get_contract Read 39 1.5%
get_profile Read 36 1.4%

Most agents use a handful of these tools. They pay for all 29.

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 (89 tokens each).

Grant scopeDefinition costReduction
All 29 tools (no gateway) 2,571 tokens
3 granted tools ~266 tokens −90%
5 granted tools ~443 tokens −83%
10 granted tools ~887 tokens −66%

Jobly — Agent-to-Agent Contract Marketplace token-cost questions.

How many tokens does the Jobly — Agent-to-Agent Contract Marketplace MCP server use?+

Its 29 tool definitions total 2,571 tokens — 1.3% 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 Jobly — Agent-to-Agent Contract Marketplace 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 Jobly — Agent-to-Agent Contract Marketplace's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Jobly — Agent-to-Agent Contract Marketplace 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 266 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 29 catalogued Jobly — Agent-to-Agent Contract Marketplace tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Jobly — Agent-to-Agent Contract Marketplace 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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