linear-mcp-lean

Get issue

get_issue

Retrieve a Linear issue by ID. Optionally fetch a richer data set including assignee, lifecycle timestamps, state type, parent, estimate, and due date.

Instructions

Retrieve a Linear issue by ID. Default → a minimal flattened field set; full:true → a documented richer superset (assignee, lifecycle timestamps, state type, parent, estimate, dueDate).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_issue"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Issue ID or identifier, e.g. ENG-123
`full`	No	Return the richer documented superset instead of the lean default

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 8, 2026

TDQS

A4.2/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose all behavioral traits. It mentions the two output modes (default minimal vs full richer set) and lists fields returned in full mode. However, it does not state that the tool is read-only, lacks permission or rate limit info, or describe error handling. This is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with two clear parts, no redundant words, and front-loads the core action. Every earned its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple endpoint with two parameters and no output schema, the description covers the main behavior and parameter meaning. It does not mention error cases, but the context is sufficient for an AI agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with descriptions for both id and full parameters. The description enhances the full parameter by listing specific fields returned (assignee, lifecycle timestamps, etc.), adding practical context beyond the schema's generic statement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Retrieve a Linear issue by ID' with a specific verb and resource, and distinguishes between default minimal fields and full richer superset. This differentiates it clearly from siblings like list_issues, save_issue, or get_issue_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving a single issue by ID, with an optional full parameter for more detail. It does not explicitly state when not to use it or mention alternatives, but the context is clear and sufficient for most agents.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.