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Atlassian Confluence MCP Server

Name: Atlassian Confluence MCP Server
Author: aashari

by aashari

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

Atlassian Confluence MCP Server

Ein Node.js/TypeScript Model Context Protocol (MCP)-Server für Atlassian Confluence Cloud. Ermöglicht KI-Systemen (z. B. LLMs wie Claude oder Cursor AI) die sichere Interaktion mit Ihren Confluence-Bereichen, -Seiten und -Inhalten in Echtzeit.

NPM-Version Build-Status

Warum diesen Server verwenden?

Minimaler Input, maximaler Output : Einfache Kennungen liefern umfassende Details, ohne dass zusätzliche Flags erforderlich sind.
Vollständiger Zugriff auf die Wissensdatenbank : Geben Sie KI-Assistenten Einblick in Dokumentationen, Wikis und Inhalte der Wissensdatenbank.
Rich Content Formatting : Automatische Konvertierung des Atlassian Document Format in lesbares Markdown.
Sichere lokale Authentifizierung : Führen Sie die Authentifizierung lokal mit Ihren Anmeldeinformationen aus und speichern Sie Token niemals auf Remote-Servern.
Intuitive Markdown-Antworten : Gut strukturierte, konsistente Markdown-Formatierung für alle Ausgaben.

Related MCP server: MCP Atlassian Server

Was ist MCP?

Model Context Protocol (MCP) ist ein offener Standard für die sichere Verbindung von KI-Systemen mit externen Tools und Datenquellen. Dieser Server implementiert MCP für Confluence Cloud und ermöglicht KI-Assistenten die programmgesteuerte Interaktion mit Ihren Confluence-Inhalten.

Voraussetzungen

Node.js (>=18.x): Herunterladen
Atlassian-Konto mit Zugriff auf Confluence Cloud

Aufstellen

Schritt 1: Holen Sie sich Ihr Atlassian API-Token

Gehen Sie zu Ihrer Atlassian API-Token-Verwaltungsseite: https://id.atlassian.com/manage-profile/security/api-tokens
Klicken Sie auf API-Token erstellen .
Geben Sie ihm eine beschreibende Bezeichnung (z. B. mcp-confluence-access ).
Klicken Sie auf Erstellen .
Kopieren Sie das generierte API-Token sofort. Sie können es nicht mehr sehen.

Schritt 2: Anmeldeinformationen konfigurieren

Option A: MCP-Konfigurationsdatei (empfohlen)

Bearbeiten oder erstellen Sie ~/.mcp/configs.json :

{
	"confluence": {
		"environments": {
			"ATLASSIAN_SITE_NAME": "<YOUR_SITE_NAME>",
			"ATLASSIAN_USER_EMAIL": "<YOUR_ATLASSIAN_EMAIL>",
			"ATLASSIAN_API_TOKEN": "<YOUR_COPIED_API_TOKEN>"
		}
	}
}

<YOUR_SITE_NAME> : Ihr Confluence-Site-Name (z. B. mycompany für mycompany.atlassian.net ).
<YOUR_ATLASSIAN_EMAIL> : Die E-Mail-Adresse Ihres Atlassian-Kontos.
<YOUR_COPIED_API_TOKEN> : Das API-Token aus Schritt 1.

Option B: Umgebungsvariablen

export ATLASSIAN_SITE_NAME="<YOUR_SITE_NAME>"
export ATLASSIAN_USER_EMAIL="<YOUR_EMAIL>"
export ATLASSIAN_API_TOKEN="<YOUR_API_TOKEN>"

Schritt 3: Installieren und Ausführen

Schnellstart mit `npx`

npx -y @aashari/mcp-server-atlassian-confluence ls-spaces

Globale Installation

npm install -g @aashari/mcp-server-atlassian-confluence
mcp-atlassian-confluence ls-spaces

Schritt 4: Mit dem AI Assistant verbinden

Konfigurieren Sie Ihren MCP-kompatiblen Client (z. B. Claude, Cursor AI):

{
	"mcpServers": {
		"confluence": {
			"command": "npx",
			"args": ["-y", "@aashari/mcp-server-atlassian-confluence"]
		}
	}
}

MCP-Tools

MCP-Tools verwenden snake_case -Namen, camelCase -Parameter und geben Antworten im Markdown-Format zurück.

conf_ls_spaces : Listet zugängliche Confluence-Bereiche auf ( type : str opt, status : str opt, limit : num opt, cursor : str opt). Verwendung: Verfügbare Bereiche anzeigen.
conf_get_space : Ruft detaillierte Space-Informationen ab ( spaceKey : str req). Verwendung: Zugriff auf Space-Inhalte und Metadaten.
conf_ls_pages : Listet Seiten mit Filterung auf ( spaceIds : str[] opt, spaceKeys : str[] opt, title : str opt, status : str[] opt, sort : str opt, limit : num opt, cursor : str opt). Verwendung: Seiten finden, die den Kriterien entsprechen.
conf_get_page : Ruft den vollständigen Seiteninhalt ab ( pageId : str req). Verwendung: Vollständigen Seiteninhalt als Markdown anzeigen.
conf_ls_page_comments : Listet Kommentare zu einer Seite auf ( pageId : str req). Verwendung: Lesen von Seitendiskussionen.
conf_search : Durchsucht Confluence-Inhalte ( cql : str opt, query : str opt, title : str opt, spaceKey : str opt, labels : str[] opt, contentType : str opt, limit : num opt, cursor : str opt). Verwendung: Suche nach bestimmten Inhalten.

`conf_ls_spaces`

Globale Bereiche auflisten:

{ "type": "global", "status": "current", "limit": 10 }

`conf_get_space`

Raumdetails abrufen:

{ "spaceKey": "DEV" }

`conf_ls_pages`

Seiten nach Bereich und Titel auflisten:

{
	"spaceKeys": ["DEV"],
	"title": "API Documentation",
	"status": ["current"],
	"sort": "-modified-date"
}

Seiten aus mehreren Bereichen auflisten:

{
	"spaceKeys": ["DEV", "HR", "MARKETING"],
	"limit": 15,
	"sort": "-modified-date"
}

`conf_get_page`

Seiteninhalt abrufen:

{ "pageId": "12345678" }

`conf_ls_page_comments`

Kommentare zur Listenseite:

{ "pageId": "12345678" }

`conf_search`

Einfache Suche:

{
	"query": "release notes Q1",
	"spaceKey": "PRODUCT",
	"contentType": "page",
	"limit": 5
}

Erweiterte CQL-Suche:

{ "cql": "space = DEV AND label = api AND created >= '2023-01-01'" }

CLI-Befehle

CLI-Befehle verwenden kebab-case . Führen Sie --help aus, um Details zu erhalten (z. B. mcp-atlassian-confluence ls-spaces --help ).

ls-spaces : Listet Leerzeichen auf ( --type , --status , --limit , --cursor ). Beispiel: mcp-atlassian-confluence ls-spaces --type global .
get-space : Ruft Space-Details ab ( --space-key ). Beispiel: mcp-atlassian-confluence get-space --space-key DEV .
ls-pages : Listet Seiten auf ( --space-keys , --title , --status , --sort , --limit , --cursor ). Beispiel: mcp-atlassian-confluence ls-pages --space-keys DEV .
get-page : Ruft den Seiteninhalt ab ( --page-id ). Beispiel: mcp-atlassian-confluence get-page --page-id 12345678 .
ls-page-comments : Listet Kommentare auf ( --page-id ). Beispiel: mcp-atlassian-confluence ls-page-comments --page-id 12345678 .
Suche : Durchsucht Inhalt ( --cql , --query , --space-key , --label , --type , --limit , --cursor ). Beispiel: mcp-atlassian-confluence search --query "security" .

Räume auflisten

Globale Bereiche auflisten:

mcp-atlassian-confluence ls-spaces --type global --status current --limit 10

Schaffen Sie Platz

mcp-atlassian-confluence get-space --space-key DEV

Listenseiten

Durch mehrere Leertasten:

mcp-atlassian-confluence ls-pages --space-keys DEV HR MARKETING --limit 15 --sort "-modified-date"

Mit Titelfilter:

mcp-atlassian-confluence ls-pages --space-keys DEV --title "API Documentation" --status current

Seite abrufen

mcp-atlassian-confluence get-page --page-id 12345678

Listenseite Kommentare

mcp-atlassian-confluence ls-page-comments --page-id 12345678

Suchen

Einfache Suche:

mcp-atlassian-confluence search --query "security best practices" --space-key DOCS --type page --limit 5

CQL-Suche:

mcp-atlassian-confluence search --cql "label = official-docs AND creator = currentUser()"

Antwortformat

Alle Antworten sind im Markdown-Format, einschließlich:

Titel : Inhaltstyp und Name.
Inhalt : Vollständiger Seiteninhalt, Suchergebnisse oder Elementliste.
Metadaten : Ersteller, Datum, Beschriftungen und andere relevante Informationen.
Paginierung : Navigationsinformationen für paginierte Ergebnisse.
Links : Verweise auf verwandte Ressourcen, sofern zutreffend.

Space List-Antwort

# Confluence Spaces

Showing **5** global spaces (current)

| Key | Name | Description |
|---|---|---|
| [DEV](#) | Development | Engineering and development documentation |
| [HR](#) | Human Resources | Employee policies and procedures |
| [MARKETING](#) | Marketing | Brand guidelines and campaign materials |
| [PRODUCT](#) | Product | Product specifications and roadmaps |
| [SALES](#) | Sales | Sales processes and resources |

*Retrieved from mycompany.atlassian.net on 2025-05-19 14:22 UTC*

Use `cursor: "next-page-token-123"` to see more spaces.

Seiteninhaltsantwort

# API Authentication Guide

**Space:** [DEV](#) (Development)
**Created by:** Jane Smith on 2025-04-01
**Last updated:** John Doe on 2025-05-15
**Labels:** api, security, authentication

## Overview

This document outlines the authentication approaches supported by our API platform.

## Authentication Methods

### OAuth 2.0

We support the following OAuth 2.0 flows:

1. **Authorization Code Flow** - For web applications
2. **Client Credentials Flow** - For server-to-server
3. **Implicit Flow** - For legacy clients only

### API Keys

Static API keys are supported but discouraged for production use due to security limitations:

| Key Type | Use Case | Expiration |
|---|---|---|
| Development | Testing | 30 days |
| Production | Live systems | 90 days |

## Implementation Examples

  import requests

  def get_oauth_token():
      return requests.post(
          'https://api.example.com/oauth/token',
          data={
              'client_id': 'YOUR_CLIENT_ID',
              'client_secret': 'YOUR_CLIENT_SECRET',
              'grant_type': 'client_credentials'
          }
      ).json()['access_token']

*Retrieved from mycompany.atlassian.net on 2025-05-19 14:25 UTC*

Entwicklung

# Clone repository
git clone https://github.com/aashari/mcp-server-atlassian-confluence.git
cd mcp-server-atlassian-confluence

# Install dependencies
npm install

# Run in development mode
npm run dev:server

# Run tests
npm test

Beitragen

Beiträge sind willkommen! Bitte:

Forken Sie das Repository.
Erstellen Sie einen Feature-Zweig ( git checkout -b feature/xyz ).
Änderungen festschreiben ( git commit -m "Add xyz feature" ).
Pushen Sie zum Zweig ( git push origin feature/xyz ).
Öffnen Sie eine Pull-Anfrage.

Weitere Einzelheiten finden Sie unter CONTRIBUTING.md .

Lizenz

ISC-Lizenz

Available Tools

5 tools

conf_deleteConfluence DELETE RequestA

Delete Confluence resources. Returns TOON format by default.

Output format: TOON (default) or JSON (outputFormat: "json")

Common operations:

/wiki/api/v2/pages/{id} - Delete page
/wiki/api/v2/blogposts/{id} - Delete blog post
/wiki/api/v2/pages/{id}/labels/{label-id} - Remove label
/wiki/api/v2/footer-comments/{id} - Delete comment
/wiki/api/v2/attachments/{id} - Delete attachment

Note: Most DELETE endpoints return 204 No Content on success.

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

ParametersJSON Schema

Name	Required	Description
`path`	Yes	The Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
`queryParams`	No	Optional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
`jq`	No	JMESPath 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
`outputFormat`	No	Output format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.

TDQS

A3.6/5.0

Behavior3/5

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

Annotations absent, so description carries full burden. It describes the action, output format (TOON), and typical response (204), but omits authorization, error handling, and irreversible nature beyond 'Delete'.

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?

Well-structured with clear sections and bullet points. Front-loaded with core action. The list of endpoints is slightly lengthy but overall concise.

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

Completeness3/5

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

Lacks output schema, so description should explain return values. Mentions TOON format and 204 response but not error handling or response structure. Missing guidance on authentication and pagination.

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

Parameters3/5

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

Schema coverage is 100%, so parameters are already documented. Description adds concrete endpoint examples for the 'path' parameter but does not significantly enhance understanding of other parameters 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?

Clearly states it deletes Confluence resources via DELETE HTTP method, with specific endpoint examples, differentiating from siblings (get, patch, post, put).

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

Usage Guidelines3/5

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

No explicit guidance on when to use this tool vs alternatives. Usage is implied by the action 'Delete' but not clarified with respect to other methods.

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

conf_getConfluence GET RequestA

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:

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

ParametersJSON Schema

Name	Required	Description
`path`	Yes	The Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
`queryParams`	No	Optional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
`jq`	No	JMESPath 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
`outputFormat`	No	Output format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.

TDQS

A4.8/5.0

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.

conf_patchConfluence PATCH RequestA

Partially update Confluence resources. Returns TOON format by default.

IMPORTANT - Cost Optimization: Use jq param to filter response fields.

Output format: TOON (default) or JSON (outputFormat: "json")

Common operations:

Update space: /wiki/api/v2/spaces/{id} body: {"name": "New Name", "description": {"plain": {"value": "Desc", "representation": "plain"}}}
Update comment: /wiki/api/v2/footer-comments/{id}

Note: Confluence v2 API primarily uses PUT for updates.

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

ParametersJSON Schema

Name	Required	Description
`path`	Yes	The Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
`queryParams`	No	Optional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
`jq`	No	JMESPath 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
`outputFormat`	No	Output format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.
`body`	Yes	Request body as a JSON object. Structure depends on the endpoint. Example for page: {"spaceId": "123", "title": "Page Title", "body": {"representation": "storage", "value": "<p>Content</p>"}}

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It discloses default output format (TOON) and cost optimization via 'jq' parameter. However, it does not discuss error handling, idempotency, authentication requirements, or side effects beyond the PATCH verb.

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 well-structured with sections and bolded notes, making key information scannable. It is somewhat verbose with examples, but each part earns its place by providing actionable guidance. Could be slightly trimmed without loss.

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?

Given no output schema, the description explains the return format (TOON or JSON) and common endpoint patterns. It covers the main use case (partial updates) and provides API reference URL. Missing details on response structure beyond format, but overall complete for a patch tool.

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?

All 5 parameters have schema descriptions (100% coverage). The description adds value by providing concrete examples for 'path' and 'body', common operations, and cost optimization context for 'jq' and 'outputFormat'. This goes beyond the schema fields.

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 'Partially update Confluence resources' and provides specific examples for updating a space and comment. The name 'conf_patch' and sibling tools ('conf_delete', 'conf_get', 'conf_post', 'conf_put') clearly differentiate it as the partial update operation.

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

Usage Guidelines3/5

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

The description mentions that Confluence v2 API primarily uses PUT for updates, which hints at when to use PATCH vs PUT, but does not explicitly state when to use this tool over alternatives. No guidance on when not to use or prerequisites beyond this subtle note.

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

conf_postConfluence POST RequestA

Create Confluence resources. Returns TOON format by default (token-efficient).

IMPORTANT - Cost Optimization:

Use jq param to extract only needed fields from response (e.g., jq: "{id: id, title: title}")
Unfiltered responses include all metadata and are expensive!

Output format: TOON (default) or JSON (outputFormat: "json")

Common operations:

Create page: /wiki/api/v2/pages body: {"spaceId": "123456", "status": "current", "title": "Page Title", "parentId": "789", "body": {"representation": "storage", "value": "Content"}}
Create blog post: /wiki/api/v2/blogposts body: {"spaceId": "123456", "status": "current", "title": "Blog Title", "body": {"representation": "storage", "value": "Content"}}
Add label: /wiki/api/v2/pages/{id}/labels - body: {"name": "label-name"}
Add comment: /wiki/api/v2/pages/{id}/footer-comments

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

ParametersJSON Schema

Name	Required	Description
`path`	Yes	The Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
`queryParams`	No	Optional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
`jq`	No	JMESPath 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
`outputFormat`	No	Output format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.
`body`	Yes	Request body as a JSON object. Structure depends on the endpoint. Example for page: {"spaceId": "123", "title": "Page Title", "body": {"representation": "storage", "value": "<p>Content</p>"}}

TDQS

A4.2/5.0

Behavior3/5

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

No annotations; description covers output format and cost implications but lacks details on authentication requirements, potential side effects, or behavior for existing resources.

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?

Well-structured with sections and front-loaded important info, but slightly verbose with repeated examples.

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?

Covers usage, cost optimization, output format, and common operations; missing auth and error handling, but references external 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. The description adds significant value with endpoint examples, body structures, and jq usage guidance beyond the 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 creates Confluence resources, with specific examples like creating pages, blog posts, labels, and comments. This distinguishes it from sibling tools (get, delete, patch, put).

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 cost optimization tips and common operation examples, but does not explicitly state when not to use the tool or compare with siblings beyond implied HTTP methods.

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

conf_putConfluence PUT RequestA

Replace Confluence resources (full update). Returns TOON format by default.

IMPORTANT - Cost Optimization:

Use jq param to extract only needed fields from response
Example: jq: "{id: id, version: version.number}"

Output format: TOON (default) or JSON (outputFormat: "json")

Common operations:

Update page: /wiki/api/v2/pages/{id} body: {"id": "123", "status": "current", "title": "Updated Title", "spaceId": "456", "body": {"representation": "storage", "value": "Content"}, "version": {"number": 2}} Note: version.number must be incremented
Update blog post: /wiki/api/v2/blogposts/{id}

Note: PUT replaces entire resource. Version number must be incremented.

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

ParametersJSON Schema

Name	Required	Description
`path`	Yes	The Confluence API endpoint path (without base URL). Must start with "/". Examples: "/wiki/api/v2/spaces", "/wiki/api/v2/pages", "/wiki/api/v2/pages/{id}"
`queryParams`	No	Optional query parameters as key-value pairs. Examples: {"limit": "25", "cursor": "...", "space-id": "123", "body-format": "storage"}
`jq`	No	JMESPath 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
`outputFormat`	No	Output format: "toon" (default, 30-60% fewer tokens) or "json". TOON is optimized for LLMs with tabular arrays and minimal syntax.
`body`	Yes	Request body as a JSON object. Structure depends on the endpoint. Example for page: {"spaceId": "123", "title": "Page Title", "body": {"representation": "storage", "value": "<p>Content</p>"}}

TDQS

A4.3/5.0

Behavior4/5

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

Despite no annotations, the description discloses key behaviors: full replacement, version increment requirement, default TOON output, and jq cost optimization. It adequately informs about operational effects.

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?

Well-structured with sections, bold headings, and bullet points. Front-loaded with purpose, then organized by cost, output, and examples. Some redundancy (version increment mentioned twice), but overall efficient.

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?

Covers main aspects for a PUT tool: purpose, parameters, common operations, output format, and token optimization. Lacks error handling or status codes, but sufficient given schema completeness.

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%, but the description adds value through examples (e.g., page update body) and explanations of jq and outputFormat, enriching understanding beyond the 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 states 'Replace Confluence resources (full update)' with specific examples for pages and blog posts, clearly distinguishing it from partial update (patch) siblings.

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 full replacements via 'full update' and 'PUT replaces entire resource', but lacks explicit comparison to conf_patch or when not to use.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

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TDQS

A4.3/5.0

Disambiguation5/5

Each tool corresponds to a distinct HTTP method (DELETE, GET, PATCH, POST, PUT), clearly differentiating their purpose. There is no overlap in functionality between tools.

Naming Consistency5/5

All tools follow the consistent pattern 'conf_' followed by the HTTP method verb in lowercase (e.g., conf_delete, conf_get). This pattern is uniform and predictable.

Tool Count5/5

With 5 tools covering the essential CRUD operations plus partial update, the count is well-scoped for a Confluence API server. It is not too few or too many.

Completeness5/5

The tools provide full coverage of basic resource lifecycle operations (create, read, update, partial update, delete). The descriptions include common API paths for pages, spaces, blog posts, etc., and the GET tool supports search via query parameters, leaving no obvious gaps.

Maintenance

ActivityInactive

ResponsivenessNo issues

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Atlassian Confluence MCP Server

Warum diesen Server verwenden?

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Voraussetzungen

Aufstellen

Schritt 1: Holen Sie sich Ihr Atlassian API-Token

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