The MCP Server enables external AI assistants to interact with your Document360 knowledge base in a structured way. These interactions do not bypass your governance model they operate within your existing version, language, and visibility configuration. Below are practical scenarios that show how different roles can use MCP in their daily documentation workflows.
Technical Writers
Problem: Researching, drafting, and refining documentation takes context-switching and manual effort
Technical writers often move between multiple articles, versions, and categories to gather context before writing or updating content. They also need to ensure consistency in tone, terminology, and structure, especially when a Style Guide is configured. Switching between the editor, search, previous versions, and reference articles slows down drafting and review.
How MCP helps
With an AI assistant connected to Document360 through MCP, writers can:
Ask the assistant to fetch relevant articles before drafting new content
Brainstorm ideas grounded in existing documentation
Refine or rewrite content directly within the documentation system
Update articles without manually copying content between tools
Use the configured Style Guide as guidance while editing or reviewing content
Instead of drafting in isolation and pasting content later, writers can work with context pulled from their own knowledge base. When updates are made, existing workflow and versioning behavior remains unchanged. Any forked revisions or review states continue to follow normal documentation processes.
Outcome
Writers reduce repetitive research, maintain better consistency across articles, and draft content faster, while staying within the same documentation governance model.
Developers
Problem: Developers need version-specific documentation while building features
Developers frequently switch between IDEs and AI-assisted coding environments such as Cursor or other AI-enabled tools. When referencing documentation, they need accurate, version-aware information without manually navigating the knowledge base.
How MCP helps
By connecting Document360 through MCP to their AI assistant within the IDE:
Developers can retrieve full article content instead of partial snippets
Search across all project versions by default, or specify a version
Access documentation in a selected language
Generate draft documentation for new endpoints or integrations
This allows documentation lookup and content creation to happen directly within the development workflow.
Outcome
Developers spend less time switching contexts and more time building with documentation that reflects the correct version and structure.
Product Managers and Consultants
Problem: Validating documentation across releases is manual and fragmented
Product managers often need to compare feature descriptions across versions, prepare release notes, or validate that documentation reflects the latest product changes. Manually checking multiple versions and categories can be slow and inconsistent.
How MCP helps
Through MCP-enabled AI assistants, product teams can:
Retrieve documentation by specific project version
Compare how features are described across releases
Identify gaps before launch
Generate structured summaries for internal alignment or onboarding
Because the interaction is structured, content is retrieved in context rather than as disconnected web output.
Outcome
Documentation becomes easier to validate before release, reducing misalignment between product updates and published knowledge.
Support Engineers
Problem: Support tickets expose knowledge gaps
When a support ticket arrives, engineers need to quickly determine whether relevant documentation already exists. Searching manually can be time-consuming, especially across multiple versions and languages. In some cases, documentation may not exist at all.
How MCP helps
With MCP connected to an AI assistant:
Support engineers can paste ticket context and ask the assistant to fetch relevant articles
Retrieve content by article name or ID
Search across versions and languages
Share article URLs directly with customers
If no relevant article is found that gap becomes visible immediately. Engineers can then:
Draft a new article based on the ticket context
Update an existing article to improve clarity
Push structured changes back into Document360
All write operations continue to respect existing workflows and permissions.
Outcome
Support teams resolve tickets faster while continuously improving documentation quality.
Use MCP with your AI assistant
After connecting MCP, you can interact with your knowledge base through your AI assistant.
Search documentation
You can ask the AI assistant to search for content in your knowledge base.
Examples:
Search for a feature in a specific version
Find articles related to a topic
Retrieve documentation in a specific language
Retrieve articles
You can request specific articles by name or topic.
The AI assistant retrieves structured content based on your project configuration, including version and language.
Create and update content
If write operations are permitted, the AI assistant can:
Create new articles in a specified category
Update existing articles
Maintain HTML structure and formatting
All write operations follow existing versioning and publishing behavior.
Access structured metadata
You can request additional context, such as:
Available project versions
Supported languages
Category structure
This helps ensure that interactions align with your documentation organization.
Best practices
Follow these best practices when using MCP with AI assistants:
Use MCP for retrieving source-of-truth documentation instead of manually copying content
Verify AI-generated responses before publishing or sharing
Specify project version or language when precision is required
Use clear and specific prompts when requesting content or updates
Ensure that user roles and permissions are configured correctly
Limitations and considerations
AI assistants can only access content permitted by your project configuration
Restricted or unpublished content remains governed by visibility rules
AI-generated outputs may require validation before use
The configuration process may vary depending on the AI assistant
MCP support may vary depending on the AI assistant or developer tool being used (such as IDE-based assistants or experimental clients). Some tools may have limited or evolving support for MCP capabilities.
Troubleshooting
If you encounter issues when using MCP:
Confirm that MCP is enabled in Document360
Verify that the MCP Server URL is correct
Ensure that OAuth authentication is completed successfully
Check whether your AI assistant supports MCP or custom connectors
If the issue persists, refer to your AI assistant documentation or contact support.