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The Srv D7aoqmh5pdvs7391dcqg MCP server costs 4,840 tokens before the first call.

Connect Srv D7aoqmh5pdvs7391dcqg and its 70 tool definitions are loaded into the model's context on every request — 2.4% of a 200k window spent before your agent does anything.

QUICK ANSWER The Srv D7aoqmh5pdvs7391dcqg MCP server's tool definitions consume 4,840 tokens — 2.5× the median MCP server (1,905 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 70 tools · 4,840 tokens · 2.4% 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 2.4%
1M WINDOW 0.5%

Corpus context: Srv D7aoqmh5pdvs7391dcqg ranks #1043 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 4,840 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 69 tokens per tool.

ToolCategoryTokens% of server
sensor_fusion Execute 238 4.9%
vla_inference Execute 137 2.8%
oracle_validate_ecg Read 134 2.8%
register_agent Write 110 2.3%
plan_motion Write 107 2.2%
execute_actions Execute 106 2.2%
simulate_trajectory Read 106 2.2%
start_rl_training Execute 102 2.1%
cardiac_issue_credential Write 99 2.0%
compare_robots Read 98 2.0%
run_calibration Execute 95 2.0%
pay_upgrade Financial 95 2.0%
cardiac_renew_key Read 94 1.9%
read_tactile Read 93 1.9%
validate_grasp Read 93 1.9%
create_finetune_dataset Write 93 1.9%
learning_log Read 92 1.9%
submit_rl_telemetry Write 91 1.9%
start_finetune_job Execute 87 1.8%
generate_scene Write 87 1.8%
process_tactile Read 86 1.8%
ros2_send_command Write 83 1.7%
check_collision Read 79 1.6%
register_robot Write 78 1.6%
cardiac_payment_process Read 76 1.6%
cardiac_register_agent Write 75 1.5%
estimate_torques Read 72 1.5%
ros2_submit_action Write 72 1.5%
task_planner Write 72 1.5%
detect_slip Read 70 1.4%
dry_run Execute 68 1.4%
query_robot_state Read 68 1.4%
update_agent Write 68 1.4%
plan_task Write 67 1.4%
execute_subtask Execute 62 1.3%
cardiac_grant_access Read 62 1.3%
get_robot_specs Read 61 1.3%
oracle_hash_ecg Read 61 1.3%
cardiac_identify_agent Read 59 1.2%
calibrate_confidence Read 58 1.2%
edge_inference Read 57 1.2%
ros2_emergency_stop Execute 56 1.2%
cardiac_check_credential Read 53 1.1%
cardiac_check_access Read 52 1.1%
oracle_verify Read 52 1.1%
learning_recommend Read 51 1.1%
list_embodiments Read 51 1.1%
get_model_info Read 50 1.0%
status_poll Read 50 1.0%
list_datasets Read 47 1.0%
get_normalization Read 45 0.9%
ros2_emergency_stop_all Execute 44 0.9%
cardiac_get_nonce Read 44 0.9%
get_test_results Read 44 0.9%
get_agent_info Read 43 0.9%
ros2_get_robot_types Read 42 0.9%
ros2_robot_status Read 40 0.8%
download_urdf Read 39 0.8%
nwo_whoami Read 39 0.8%
robot_query Read 39 0.8%
discover_capabilities Read 37 0.8%
get_agent_status Read 37 0.8%
check_balance Read 36 0.7%
oracle_health Read 36 0.7%
create_wallet Write 36 0.7%
get_scene_library Read 35 0.7%
list_models Read 34 0.7%
ros2_list_robots Read 34 0.7%
get_streaming_config Read 33 0.7%
nwo_health Read 30 0.6%

Most agents use a handful of these tools. They pay for all 70.

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 (69 tokens each).

Grant scopeDefinition costReduction
All 70 tools (no gateway) 4,840 tokens
3 granted tools ~207 tokens −96%
5 granted tools ~346 tokens −93%
10 granted tools ~691 tokens −86%

Srv D7aoqmh5pdvs7391dcqg token-cost questions.

How many tokens does the Srv D7aoqmh5pdvs7391dcqg MCP server use?+

Its 70 tool definitions total 4,840 tokens — 2.4% 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 Srv D7aoqmh5pdvs7391dcqg 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 Srv D7aoqmh5pdvs7391dcqg's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Srv D7aoqmh5pdvs7391dcqg 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 207 tokens, a 96% 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 70 catalogued Srv D7aoqmh5pdvs7391dcqg tools. Counts refresh with every site build.

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

A PolicyLayer grant scopes Srv D7aoqmh5pdvs7391dcqg 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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