// MCP TOKEN COST

The Leaper Vision Toolkit MCP server costs 65,642 tokens before the first call.

Connect Leaper Vision Toolkit and its 169 tool definitions are loaded into the model's context on every request — 33% of a 200k window spent before your agent does anything.

QUICK ANSWER The Leaper Vision Toolkit MCP server's tool definitions consume 65,642 tokens — 61× the median MCP server (1,075 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 169 tools · 65,642 tokens · 33% of 200k · 6.6% 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 33%

1M WINDOW 6.6%

Corpus context: Leaper Vision Toolkit ranks #4 of 1,659 measured MCP servers by definition cost. The median is 1,075 tokens, p90 is 6,119, and the heaviest (Fusionauth) is 183,337 — 92% of a 200k window on its own.

// PER-TOOL BREAKDOWN

Where the 65,642 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 388 tokens per tool.

Tool	Category	Tokens	% of server
il_blob_analysis_color	Execute	1,430	2.2%
il_blob_analysis	Execute	1,381	2.1%
edge_filter_set_edge_polarity	Write	1,152	1.8%
pat_match_learn_with_shape	Write	1,022	1.6%
il_histogram_build_draw	Execute	956	1.5%
image_compare_compare	Write	898	1.4%
edge_filter_set_edge_kernel	Write	837	1.3%
pat_match_learn_with_shape_image	Write	833	1.3%
image_compare_set_baseline	Write	813	1.2%
il_image_morph_set_morph_shape	Write	805	1.2%
image_stats_count_pixel_color	Read	789	1.2%
pat_match_set_pat_center	Write	723	1.1%
pat_match_prune	Write	718	1.1%
image_compare_compare_symmetric	Write	711	1.1%
image_convert_convert	Write	700	1.1%
pat_match_learn	Write	666	1.0%
display_match	Write	643	1.0%
image_convert_color_map_multi_band	Write	639	1.0%
display_line_detector	Write	638	1.0%
il_region_subtract	Write	630	1.0%
display_blob_analysis	Write	605	0.9%
display_circle_detector	Write	602	0.9%
il_region_add	Write	600	0.9%
il_region_union	Write	600	0.9%
il_image_op_scale_rotate	Execute	595	0.9%
il_region_xor	Write	591	0.9%
image_convert_convert_color	Write	585	0.9%
il_region_intersect	Write	571	0.9%
il_line_detector_set_polarity	Write	567	0.9%
il_circle_detector_set_polarity	Write	563	0.9%
image_stats_count_pixel	Read	561	0.9%
il_image_op_normalize_mean_std_dev	Write	559	0.9%
image_convert_color_map	Write	555	0.8%
il_image_op_normalize	Write	547	0.8%
il_histogram_build_min_max	Execute	536	0.8%
il_histogram_build_items	Execute	524	0.8%
il_histogram_build_mean_std_dev	Execute	518	0.8%
image_set_to_color	Write	507	0.8%
image_copy_from	Write	495	0.8%
image_set_to	Write	482	0.7%
il_region_to_mask	Write	480	0.7%
image_stats_min	Write	468	0.7%
image_stats_sharpness	Write	467	0.7%
il_region_rotate_and_translate	Read	466	0.7%
image_stats_max	Write	464	0.7%
il_image_morph_bottom_hat	Destructive	459	0.7%
pat_match_get_pat_shape	Read	457	0.7%
pat_match_get_pat_feature	Read	436	0.7%
il_image_filter_set_kernel_sigma	Write	430	0.7%
il_image_op_split	Write	420	0.6%
il_region_scale	Execute	418	0.6%
pat_match_get_pat_center_mode	Read	409	0.6%
il_line_detector_set_find_by	Write	408	0.6%
il_region_rotate	Write	407	0.6%
il_circle_detector_set_find_by	Write	404	0.6%
il_image_op_resize	Write	399	0.6%
pat_match_new	Execute	395	0.6%
il_image_threshold_binarize	Execute	392	0.6%
il_image_op_resize_to	Write	391	0.6%
il_image_threshold_set_threshold_adapt_local	Write	384	0.6%
il_image_filter_linear_filter	Write	382	0.6%
il_image_threshold_set_threshold	Write	381	0.6%
il_image_op_rotate	Write	379	0.6%
il_image_threshold_stretch	Execute	378	0.6%
pat_match_get_pat_center	Read	372	0.6%
il_image_filter_set_kernel_size	Write	371	0.6%
image_stats_mean_std_dev	Write	368	0.6%
il_image_op_blend	Write	367	0.6%
image_convert_bgr_mix	Write	364	0.6%
il_image_filter_edge_preserve_denoise	Write	363	0.6%
il_image_filter_edge_preserve_texture_enhance	Write	363	0.6%
il_region_translate	Read	362	0.6%
image_info	Read	362	0.6%
il_image_filter_linear_filter_abs	Write	362	0.6%
il_image_threshold_set_threshold_adapt_globald	Write	349	0.5%
edge_filter_gradient_full	Write	339	0.5%
edge_filter_gradient_v	Write	338	0.5%
il_line_detector_set_edge_width	Write	338	0.5%
edge_filter_gradient_h	Write	333	0.5%
il_circle_detector_set_edge_width	Write	333	0.5%
il_region_invert	Write	331	0.5%
il_image_op_add_scalar	Write	329	0.5%
il_image_op_project_y	Write	328	0.5%
image_convert_depth16_to8	Write	328	0.5%
il_image_morph_open	Write	326	0.5%
il_image_op_project_x	Write	326	0.5%
il_annulus_sector_region	Execute	321	0.5%
il_image_morph	Write	319	0.5%
il_image_morph_top_hat	Write	318	0.5%
il_image_op_tile_y	Write	318	0.5%
il_image_op_tile_x	Write	316	0.5%
il_image_op_split_y	Write	314	0.5%
pat_match_get_pat_prune_mask	Read	313	0.5%
il_image_op_split_x	Write	313	0.5%
edge_filter_new	Execute	312	0.5%
il_image_morph_dilate	Write	312	0.5%
il_image_morph_erode	Write	312	0.5%
il_image_morph_gradient	Write	312	0.5%
il_image_morph_close	Write	311	0.5%
il_line_detector_set_accept_score	Write	311	0.5%
il_circle_detector_set_accept_score	Write	307	0.5%
il_image_morph_top_bottom_hat	Write	303	0.5%
il_line_detector_set_norm_score	Write	297	0.5%
il_circle_detector_set_norm_score	Write	292	0.4%
pat_match_get_pat_mask	Read	291	0.4%
il_image_filter_optical_density	Write	284	0.4%
il_image_filter_local_median_norm	Write	283	0.4%
il_image_op_flip	Write	283	0.4%
il_image_filter_sharpen	Write	275	0.4%
il_line_detector_set_max_count	Write	275	0.4%
il_circle_detector_set_max_count	Write	272	0.4%
il_image_filter_fill_hole	Write	272	0.4%
il_image_op_bit_xor_scalar	Write	271	0.4%
il_image_op_min_scalar	Write	271	0.4%
il_ellipse_region	Write	270	0.4%
il_image_op_max_scalar	Write	270	0.4%
il_image_op_bit_and_scalar	Write	269	0.4%
il_image_op_bit_or_scalar	Write	269	0.4%
il_image_op_multiply_scalar	Write	267	0.4%
il_image_op_diff_scalar	Write	266	0.4%
il_image_op_divide_scalar	Write	266	0.4%
il_image_op_sub_scalar	Write	266	0.4%
il_rot_rect_region	Write	261	0.4%
il_rect_region	Write	257	0.4%
pat_match_get_pat_image	Read	256	0.4%
pat_match_is_learnt	Read	256	0.4%
image_set_channel	Write	253	0.4%
il_image_filter_equalize	Write	251	0.4%
il_image_filter_local_median	Write	247	0.4%
image_convert_bgr_to_gray	Write	247	0.4%
get_tool_tree	Read	244	0.4%
il_image_op_add_weighted	Write	238	0.4%
image_compare_new	Execute	236	0.4%
il_image_filter_high_pass	Write	236	0.4%
il_image_filter_mean_filter	Write	236	0.4%
image_set_size	Write	236	0.4%
il_annulus_region	Write	229	0.3%
image_convert_gray_to_bgr	Write	228	0.3%
il_image_filter_gaussian	Write	218	0.3%
il_mask_region	Write	210	0.3%
il_image_op_divide	Write	197	0.3%
image_new	Execute	196	0.3%
il_poly_region	Write	192	0.3%
il_image_threshold	Write	190	0.3%
image_get_channel	Read	187	0.3%
il_image_op_min	Write	186	0.3%
il_circle_region	Write	185	0.3%
il_image_op_bit_and	Write	185	0.3%
il_image_op_max	Write	185	0.3%
il_image_filter	Write	183	0.3%
il_image_op_multiply	Write	182	0.3%
il_line_detector	Write	182	0.3%
il_image_op_sub	Write	181	0.3%
il_circle_detector	Write	179	0.3%
il_image_op_gain_offset	Write	178	0.3%
il_image_op_log	Write	175	0.3%
il_image_op_bit_xor	Write	173	0.3%
il_image_op_bit_or	Write	171	0.3%
ilocr_ib_detect	Read	170	0.3%
il_image_op_add	Write	170	0.3%
il_image_op_diff	Write	168	0.3%
il_image_op_pow	Write	168	0.3%
il_image_op_invert	Write	159	0.2%
il_image_op_bit_not	Write	147	0.2%
image_convert_normalize_to16	Write	141	0.2%
image_convert_normalize_to8	Write	141	0.2%
image_convert_bgr_to_gray_color	Write	122	0.2%
image_convert_depth8_to16	Write	118	0.2%
image_convert_gray_to_bgr_color	Write	98	0.1%

// SCOPED GRANT

Most agents use a handful of these tools. They pay for all 169.

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 (388 tokens each).

Grant scope	Definition cost	Reduction
All 169 tools (no gateway)	65,642 tokens	—
3 granted tools	~1,165 tokens	−98%
5 granted tools	~1,942 tokens	−97%
10 granted tools	~3,884 tokens	−94%

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

//FAQ

Leaper Vision Toolkit token-cost questions.

How many tokens does the Leaper Vision Toolkit MCP server use?+

Its 169 tool definitions total 65,642 tokens — 33% 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 Leaper Vision Toolkit 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 Leaper Vision Toolkit's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Leaper Vision Toolkit 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 1,165 tokens, a 98% 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 05-06-2026 from the PolicyLayer scan database over all 169 catalogued Leaper Vision Toolkit tools. Counts refresh with every site build.