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aashari

Atlassian Confluence MCP Server

by aashari

Confluence GET Request

conf_get

Read any Confluence data with token-efficient output by specifying JMESPath filters to reduce response size.

Instructions

Read any Confluence 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 limit query param to restrict result count (e.g., limit: "5")

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

Schema Discovery Pattern:

  1. First call: path: "/wiki/api/v2/spaces", queryParams: {"limit": "1"} (no jq) - explore available fields

  2. Then use: jq: "results[*].{id: id, key: key, name: name}" - extract only what you need

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

Common paths:

  • /wiki/api/v2/spaces - list spaces

  • /wiki/api/v2/pages - list pages (use space-id query param)

  • /wiki/api/v2/pages/{id} - get page details

  • /wiki/api/v2/pages/{id}/body - get page body (body-format: storage, atlas_doc_format, view)

  • /wiki/rest/api/search - search content (cql query param)

JQ examples: results[*].id, results[0], results[*].{id: id, title: title}

API reference: https://developer.atlassian.com/cloud/confluence/rest/v2/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesThe Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
queryParamsNoOptional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
jqNoJMESPath expression to filter/transform the response. IMPORTANT: Always use this to extract only needed fields and reduce token costs. Examples: "results[*].{id: id, title: title}" (extract specific fields), "results[0]" (first result), "results[*].id" (IDs only). See https://jmespath.org
outputFormatNoOutput format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.
Behavior4/5

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

No annotations provided, so description carries full burden. It fully discloses behavior: returns TOON format by default (30-60% fewer tokens), explains cost implications, and provides a schema discovery pattern. However, it does not mention error handling, authentication requirements, or rate limiting. Could be slightly more transparent on edge cases but sufficient for a read tool.

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?

Well-structured with clear sections (IMPORTANT - Cost Optimization, Schema Discovery Pattern, Output format, Common paths, JQ examples). Front-loaded with core purpose and crucial cost advice. Every sentence adds value; no fluff. Appropriately detailed for a complex tool without being verbose.

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?

Comprehensive given no output schema: explains output format, how to control it, provides common paths, discovery pattern, and jq examples. With 4 parameters and no output schema, the description fully equips an agent to use the tool effectively, including cost optimization. Sibling tools are all write, reinforcing the read-only nature.

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% but description adds significant value beyond schema: explains `jq` with cost-saving context, contrasts `outputFormat` options, gives concrete examples for `path` and `queryParams`. Each parameter is well-contextualized in the tool's usage, making it easier for the agent to choose correct values.

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?

Starts with 'Read any Confluence data', clearly describing the tool as a read-only GET request. Differentiates from sibling tools (conf_delete, conf_patch, conf_post, conf_put) which are all write operations. Also specifies output format (TOON by default) and token efficiency.

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

Usage Guidelines5/5

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

Provides extensive usage guidelines: strongly recommends using `jq` and `limit` to reduce costs, outlines a discovery pattern for exploring schemas, lists common paths with examples, and gives jq examples. Explicitly advises on when to use this tool for reading and implies not for writing by nature of being a GET tool.

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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