This server allows interaction with Confluence, providing tools to search, retrieve, and update pages:
Search Confluence pages: Execute CQL queries to find pages using execute_cql_search
Retrieve page content: Fetch the content of a specific page using its ID via get_page_content
Update page content: Modify a page's content and optionally its title using update_page_content
Provides tools for searching Confluence pages using CQL queries and retrieving page content, enabling access to information stored in Confluence wikis.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Confluence Communication Server search for pages about Q4 marketing strategy"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Interact with Confluence
This is a TypeScript-based MCP server that provides tools to interact with Confluence. It demonstrates core MCP concepts by providing:
Tools for executing CQL queries to search pages
Tools for retrieving the content of Confluence pages
Tools for updating content on Confluence pages
Related MCP server: Confluence MCP Server
execute_cql_searchPurpose: Run a CQL query to search for Confluence pages.
Parameters: cql, limit (default: 10).
get_page_contentPurpose: Fetch the content of a Confluence page.
Parameters: pageId.
update_page_contentPurpose: Update the content of a Confluence page.
Parameters: pageId, content, title (optional, if you want to change it).
Install dependencies:
npm installBuild the server:
npm run buildFor development with auto-rebuild:
npm run watchTo install Confluence Communication Server MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @KS-GEN-AI/confluence-mcp-server --client claudeTo use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"Confluence communication server": {
"command": "node",
"args": ["/PATH_TO_THE_PROJECT/build/index.js"],
"env": {
"CONFLUENCE_URL": "https://XXXXXXXX.atlassian.net/wiki",
"CONFLUENCE_API_MAIL": "Your email",
"CONFLUENCE_API_KEY": "KEY_FROM: https://id.atlassian.com/manage-profile/security/api-tokens"
}
}
}
}Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspectorThe Inspector will provide a URL to access debugging tools in your browser.
Execute a CQL query on Confluence to search pages
| Name | Required | Description | Default |
|---|---|---|---|
| cql | Yes | CQL query string | |
| limit | No | Number of results to return |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool executes a CQL query, it doesn't describe what happens during execution - whether it's read-only, what permissions are required, how results are structured, whether there are rate limits, or what errors might occur. For a search tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without any wasted words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place in conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (search results format), what happens on execution, or provide any context about CQL query capabilities. For a tool that executes queries against a complex system like Confluence, more context about behavior and results is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters (cql query string and limit with default). The description adds no additional parameter information beyond what's in the schema - it doesn't explain CQL syntax, provide query examples, or clarify the limit parameter's behavior. The baseline 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute a CQL query') and target resource ('on Confluence to search pages'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like get_page_content or update_page_content, which appear to be different operations rather than alternative search methods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool versus alternatives. There's no mention of when this search method is appropriate, what types of queries it supports, or how it differs from other search approaches. The sibling tools appear to be for different purposes (getting/updating content rather than searching), but this distinction isn't explained.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the content of a Confluence page
| Name | Required | Description | Default |
|---|---|---|---|
| pageId | Yes | Confluence Page ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't cover aspects like authentication needs, rate limits, error handling, or what the returned content includes (e.g., format, metadata), which are critical for a read operation in a system like Confluence.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that retrieves content from a complex system like Confluence. It doesn't explain what the returned content entails (e.g., HTML, text, attachments) or any behavioral nuances, leaving significant gaps for the agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'pageId' fully documented in the schema. The description doesn't add any extra meaning about the parameter beyond what the schema provides, such as how to obtain the pageId or its format, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('content of a Confluence page'), making the purpose immediately understandable. It distinguishes from siblings like 'update_page_content' by specifying retrieval rather than modification, though it doesn't explicitly contrast with 'execute_cql_search' for broader searches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While it implies usage for retrieving specific page content, it doesn't mention when to choose this over 'execute_cql_search' for finding pages or 'update_page_content' for editing, leaving the agent without explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Update the content of a Confluence page
| Name | Required | Description | Default |
|---|---|---|---|
| pageId | Yes | Confluence Page ID | |
| content | Yes | HTML content to update the page with | |
| title | No | Page title (optional, if you want to change it) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'update' which implies a mutation, but doesn't disclose critical traits like required permissions, whether changes are reversible, rate limits, or what happens on success/failure. This leaves significant gaps for a tool that modifies content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral context (e.g., permissions, side effects), usage guidelines, and details on return values or errors. For updating page content, this leaves too many unknowns for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all parameters (pageId, content, title). The description adds no additional meaning beyond what the schema provides, such as format details for content or title constraints. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and resource 'content of a Confluence page', making the purpose immediately understandable. It distinguishes from sibling tools like 'get_page_content' (read vs. write) and 'execute_cql_search' (search vs. update), though it doesn't explicitly mention these distinctions in the description itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing page ID), exclusions, or compare it to sibling tools like 'get_page_content' for reading or 'execute_cql_search' for finding pages. Usage is implied by the action but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
execute_cql_searchget_page_contentupdate_page_contentEach tool has a clearly distinct purpose: execute_cql_search handles search queries, get_page_content retrieves page content, and update_page_content modifies page content. There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.
All tools follow a consistent verb_noun pattern (execute_cql_search, get_page_content, update_page_content) with clear action verbs and descriptive nouns. This uniformity enhances readability and predictability across the tool set.
With only 3 tools, the set feels thin for a Confluence server, lacking operations like creating or deleting pages, managing comments, or handling attachments. While the tools cover basic read/update/search, the scope is limited and may require workarounds for full domain coverage.
The tool set is significantly incomplete for Confluence communication, missing essential CRUD operations such as create_page and delete_page, as well as functionalities for comments, spaces, or user management. This will likely cause agent failures when attempting comprehensive workflows.
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