// MCP TOKEN COST

The Linear MCP server costs 7,149 tokens before the first call.

Connect Linear and its 66 tool definitions are loaded into the model's context on every request — 3.6% of a 200k window spent before your agent does anything.

QUICK ANSWER The Linear MCP server's tool definitions consume 7,149 tokens — 6.7× the median MCP server (1,075 tokens). A scoped grant exposing only the tools you use cuts that roughly in proportion.

MEASURED FROM SCHEMAS 66 tools · 7,149 tokens · 3.6% of 200k · 0.7% 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 3.6%

1M WINDOW 0.7%

Corpus context: Linear ranks #142 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 7,149 tokens go.

Each row is one tool definition as a tools/list entry — name, description and input schema — counted with o200k_base. Average: 108 tokens per tool.

Tool	Category	Tokens	% of server
linear_updateIssue	Write	459	6.4%
update_issue	Write	394	5.5%
list_issues	Read	389	5.4%
create_issue	Write	386	5.4%
linear_createIssue	Write	359	5.0%
list_documents	Read	282	3.9%
list_projects	Read	240	3.4%
list_teams	Read	238	3.3%
create_project	Write	190	2.7%
update_project	Write	185	2.6%
linear_updateInitiative	Write	179	2.5%
linear_createInitiative	Write	165	2.3%
create_issue_label	Write	157	2.2%
linear_searchIssues	Read	152	2.1%
list_issue_labels	Read	150	2.1%
linear_createProject	Write	133	1.9%
linear_createIssueRelation	Write	132	1.8%
linear_updateProject	Write	126	1.8%
list_my_issues	Read	119	1.7%
linear_createComment	Write	102	1.4%
linear_setIssuePriority	Write	102	1.4%
get_issue_status	Read	83	1.2%
list_cycles	Read	83	1.2%
linear_convertIssueToSubtask	Write	83	1.2%
linear_assignIssue	Write	79	1.1%
linear_removeIssueLabel	Destructive	78	1.1%
linear_addIssueLabel	Write	78	1.1%
linear_getIssueHistory	Read	77	1.1%
linear_getComments	Read	76	1.1%
create_comment	Write	75	1.0%
linear_transferIssue	Financial	72	1.0%
linear_addIssueToProject	Write	70	1.0%
linear_getCycles	Read	69	1.0%
linear_getInitiativeById	Read	69	1.0%
linear_getInitiatives	Read	69	1.0%
linear_addIssueToCycle	Write	69	1.0%
linear_getProjectIssues	Read	68	1.0%
linear_getWorkflowStates	Read	67	0.9%
linear_getInitiativeProjects	Read	65	0.9%
linear_removeProjectFromInitiative	Destructive	62	0.9%
linear_getIssueById	Read	62	0.9%
linear_addProjectToInitiative	Write	62	0.9%
search_documentation	Read	59	0.8%
linear_subscribeToIssue	Write	53	0.7%
linear_getActiveCycle	Read	49	0.7%
linear_getIssues	Read	49	0.7%
linear_archiveIssue	Write	49	0.7%
linear_duplicateIssue	Write	49	0.7%
get_team	Read	47	0.7%
linear_deleteInitiative	Destructive	46	0.6%
get_issue	Read	46	0.6%
get_project	Read	45	0.6%
get_user	Read	44	0.6%
linear_unarchiveInitiative	Write	44	0.6%
list_issue_statuses	Read	43	0.6%
list_users	Read	43	0.6%
get_document	Read	41	0.6%
linear_archiveInitiative	Write	41	0.6%
list_comments	Read	39	0.5%
linear_getUsers	Read	31	0.4%
linear_getLabels	Read	30	0.4%
list_project_labels	Read	30	0.4%
linear_getOrganization	Read	29	0.4%
linear_getProjects	Read	29	0.4%
linear_getTeams	Read	29	0.4%
linear_getViewer	Read	29	0.4%

// SCOPED GRANT

Most agents use a handful of these tools. They pay for all 66.

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 (108 tokens each).

Grant scope	Definition cost	Reduction
All 66 tools (no gateway)	7,149 tokens	—
3 granted tools	~325 tokens	−95%
5 granted tools	~542 tokens	−92%
10 granted tools	~1,083 tokens	−85%

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

//FAQ

Linear token-cost questions.

How many tokens does the Linear MCP server use?+

Its 66 tool definitions total 7,149 tokens — 3.6% 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 Linear 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 Linear's token usage?+

Expose fewer tools. A PolicyLayer grant scopes Linear 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 325 tokens, a 95% 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 66 catalogued Linear tools. Counts refresh with every site build.