mcp-context-cost

mcp-atlassian — context cost

17,311 tokens across 63 tools — heavy (15–30K). Measured 2026-08-16 under methodology v1.0.

   
server (self-reported) Atlassian MCP v3.4.7
status dynamic
tokenizer tiktoken / o200k_base
launch command uvx mcp-atlassian
isolation docker · ghcr.io/astral-sh/uv:python3.12-bookworm-slim · network bridge · network enabled for package fetch; clean FS, no host credentials
env vars supplied JIRA_URL, JIRA_USERNAME, JIRA_API_TOKEN
canonical SHA-256 c55fb33bea2aebc0be1aa5c7a04e19652f01508e0891e8fdf705684f5de3ce85
category community
source https://github.com/sooperset/mcp-atlassian

This server’s tools/list differed between two consecutive captures, so the number is the first capture and moves between sweeps. Treat it as a range, not a constant.

Where the tokens are

tool tokens share description schema
jira_update_proforma_form_answers 800 4.6% 507 145
jira_update_issue 602 3.5% 18 502
jira_get_issue 567 3.3% 54 428
jira_search 555 3.2% 12 461
jira_create_issue 550 3.2% 15 453
jira_create_customer_request 464 2.7% 8 370
jira_get_issue_sla 463 2.7% 161 201
jira_get_board_issues 437 2.5% 13 338
jira_search_assignable_users 434 2.5% 160 180
jira_get_field_options 402 2.3% 76 234
jira_create_issue_link 391 2.3% 8 299
jira_create_remote_issue_link 377 2.2% 56 231
jira_add_worklog 363 2.1% 10 268
jira_transition_issue 355 2.1% 9 264
jira_add_comment 340 2.0% 8 251
jira_move_issue 312 1.8% 87 133
jira_batch_create_issues 308 1.8% 8 214
jira_update_version 306 1.8% 48 174
jira_batch_create_versions 290 1.7% 9 197
jira_get_issue_development_info 288 1.7% 51 144
jira_get_agile_boards 280 1.6% 13 180
jira_get_issues_development_info 274 1.6% 27 152
jira_batch_get_changelogs 264 1.5% 12 160
jira_get_sprint_issues 261 1.5% 6 168
jira_get_project_epic_hierarchy 261 1.5% 72 92
jira_assign_issue 256 1.5% 46 126
jira_update_sprint 251 1.4% 4 164
jira_get_issue_dates 248 1.4% 38 122
jira_edit_comment 242 1.4% 9 152
jira_get_create_fields 242 1.4% 59 95

33 smaller tools omitted (6,189 tokens combined) — all of them are in the raw capture.

Each tool is tokenized on its own, so the parts do not sum exactly to the whole: the array adds its own brackets and commas, and the tokenizer merges tokens across object boundaries. The badge number is always the count of the whole array, never a sum of parts.

What this costs on Claude

Measured 2026-08-16 against claude-opus-5 via Anthropic’s count_tokens (method tools-delta/v1).

  tokens  
o200k, full capture 17,311 the badge number — every byte tools/list returned
o200k, Anthropic fields only 12,823 25.9% of the capture is MCP-only metadata
Claude, same fields 22,234 1.28× the badge number

An Anthropic tool definition carries name, description, and input_schema and nothing else, so title, annotations, outputSchema, execution, and icons are dropped before the request — that is the second row. The third row is the same tools counted by Anthropic, which is larger than the second because Anthropic’s tokenizer is denser on this content than o200k_base and the API adds its own framing (at most 328 tokens of it fixed, measured against a single minimal tool). The two effects run in opposite directions, which is why the Claude number is not a fixed multiple of the badge.

Re-derive it

npx -y mcp-context-cost verify results/mcp-atlassian/measurement.json

That re-tokenizes the published capture and checks the count and the hash. If it disagrees with the badge, the badge is wrong — open an issue and it gets corrected.

Badge JSON · All servers · Leaderboard · Methodology