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mcp-server-atlassian-jira

by asky74
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TypeScript
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Jira GET Request

jira_get
Read-only

Read Jira data using REST API. Supports JQL search, issue details, comments, and worklogs. Filter response fields with jq to minimize token usage.

Instructions

Read any Jira data. Returns TOON format by default (30-60% fewer tokens than JSON).

IMPORTANT - Cost Optimization:

  • ALWAYS use jq param to filter response fields. Unfiltered responses are very expensive!

  • Use maxResults query param to restrict result count (e.g., maxResults: "5")

  • If unsure about available fields, first fetch ONE item with maxResults: "1" and NO jq filter to explore the schema, then use jq in subsequent calls

Schema Discovery Pattern:

  1. First call: path: "/rest/api/3/search/jql", queryParams: {"maxResults": "1", "jql": "project=PROJ"} (no jq) - explore available fields

  2. Then use: jq: "issues[*].{key: key, summary: fields.summary, status: fields.status.name}" - extract only what you need

Output format: TOON (default, token-efficient) or JSON (outputFormat: "json")

Common paths:

  • /rest/api/3/project - list all projects

  • /rest/api/3/project/{projectKeyOrId} - get project details

  • /rest/api/3/search/jql - search issues with JQL (use jql query param). NOTE: /rest/api/3/search is deprecated!

  • /rest/api/3/issue/{issueIdOrKey} - get issue details

  • /rest/api/3/issue/{issueIdOrKey}/comment - list issue comments

  • /rest/api/3/issue/{issueIdOrKey}/worklog - list issue worklogs

  • /rest/api/3/issue/{issueIdOrKey}/transitions - get available transitions

  • /rest/api/3/user/search - search users (use query param)

  • /rest/api/3/status - list all statuses

  • /rest/api/3/issuetype - list issue types

  • /rest/api/3/priority - list priorities

JQ examples: issues[*].key, issues[0], issues[*].{key: key, summary: fields.summary}

Example JQL queries: project=PROJ, assignee=currentUser(), status="In Progress", created >= -7d

API reference: https://developer.atlassian.com/cloud/jira/platform/rest/v3/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jqNoJMESPath expression to filter/transform the response. IMPORTANT: Always use this to extract only needed fields and reduce token costs. Examples: "issues[*].{key: key, summary: fields.summary}" (extract specific fields), "issues[0]" (first result), "issues[*].key" (keys only). See https://jmespath.org
pathYesThe Jira API endpoint path (without base URL). Must start with "/". Examples: "/rest/api/3/project", "/rest/api/3/search/jql", "/rest/api/3/issue/{issueIdOrKey}"
queryParamsNoOptional query parameters as key-value pairs. Examples: {"maxResults": "50", "startAt": "0", "jql": "project=PROJ", "fields": "summary,status"}
outputFormatNoOutput format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint. Description adds significant behavioral details: default TOON output format, token efficiency, cost warnings, deprecation notice for '/rest/api/3/search', and schema exploration workflow. All consistent with annotations.

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

Conciseness4/5

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

The description is lengthy but well-structured with headings, bullet points, and code examples. Every section adds value (purpose, cost optimization, schema discovery, common paths, examples). Minor redundancy (jq examples appear twice) but overall efficient.

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

Completeness5/5

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

For a GET tool with 4 params and no output schema, the description is remarkably complete: return format, cost optimization, schema discovery pattern, common paths, example requests, JQL syntax, API reference link. An agent can confidently invoke this tool without additional documentation.

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

Parameters5/5

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

Schema coverage is 100% with descriptions. Description adds extensive context: jq examples, common path list, query parameter examples (maxResults, jql), output format explanation (TOON vs JSON), and JQL query examples. Goes well beyond schema.

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 clearly states the tool performs GET requests to read Jira data, with 'Read any Jira data.' and a title 'Jira GET Request'. It distinguishes from sibling write tools (jira_post, jira_patch, etc.) by its read-only nature.

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?

Provides explicit cost optimization guidance (use jq, maxResults), a schema discovery pattern, and common paths. Does not explicitly state when not to use this tool, but sibling tools are all write operations so differentiation is clear.

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

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