Home / Token cost / Taskflow

The Taskflow MCP server costs 5,155 tokens before the first call.

Connect Taskflow and its 50 tool definitions are loaded into the model's context on every request — 2.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The Taskflow MCP server's tool definitions consume 5,155 tokens — 2.7× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 50 tools · 5,155 tokens · 2.6% of 200k · 0.5% 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 2.6%
1M WINDOW 0.5%

Corpus context: Taskflow ranks #1013 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 5,155 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 103 tokens per tool.

ToolCategoryTokens% of server
update_task Write 290 5.6%
send_keys Write 222 4.3%
ask_agent Read 212 4.1%
create_task Write 209 4.1%
ask_user Read 203 3.9%
log_debug Read 190 3.7%
broadcast_agents Write 186 3.6%
bulk_create_tasks Write 168 3.3%
compact_activity_log Read 151 2.9%
send_to_agent Write 125 2.4%
bootstrap Read 123 2.4%
list_tasks Read 120 2.3%
get_tool_stats Read 111 2.2%
get_setting Read 107 2.1%
get_task_cost Read 107 2.1%
update_setting Write 101 2.0%
stop_timer Execute 100 1.9%
respond_to_message Read 100 1.9%
update_project Write 96 1.9%
update_task_status Write 96 1.9%
check_response Read 92 1.8%
create_checkpoint Write 91 1.8%
create_project Write 90 1.7%
capture_terminal Read 89 1.7%
get_agent_instructions Read 88 1.7%
register_agent Write 86 1.7%
get_activity_log Read 83 1.6%
get_timeline Read 82 1.6%
get_analytics Read 81 1.6%
get_checkpoint Read 79 1.5%
start_timer Execute 77 1.5%
list_sessions Read 77 1.5%
check_broadcast Read 74 1.4%
list_agents Read 74 1.4%
pause_timer Read 73 1.4%
delete_project Destructive 68 1.3%
get_project Read 68 1.3%
get_task Read 68 1.3%
list_notifications Read 67 1.3%
delete_task Destructive 65 1.3%
list_checkpoints Read 65 1.3%
search_tasks Read 65 1.3%
clear_data Destructive 62 1.2%
search_projects Read 62 1.2%
mark_notification_read Write 58 1.1%
mark_all_notifications_read Write 56 1.1%
list_projects Read 52 1.0%
clear_activity_log Destructive 50 1.0%
check_messages Read 49 1.0%
clear_notifications Destructive 47 0.9%

Most agents use a handful of these tools. They pay for all 50.

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 (103 tokens each).

Grant scopeDefinition costReduction
All 50 tools (no gateway) 5,155 tokens
3 granted tools ~309 tokens −94%
5 granted tools ~516 tokens −90%
10 granted tools ~1,031 tokens −80%

Taskflow token-cost questions.

How many tokens does the Taskflow MCP server use?+

Its 50 tool definitions total 5,155 tokens — 2.6% 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 Taskflow 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 Taskflow's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Taskflow 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 309 tokens, a 94% 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 50 catalogued Taskflow tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Taskflow 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.