analytics-dataproductivity

WikiJS

ricardocenci

by ricardocenci

Integrate with WikiJS to search, retrieve, and explore multilingual wiki content using advanced GraphQL-based operations

Integrates with WikiJS knowledge bases through GraphQL to enable search, page retrieval, and content discovery operations across multilingual wiki deployments with structured metadata and filtering capabilities.

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    what it does

    Integrates with WikiJS knowledge bases through GraphQL to enable search, page retrieval, and content discovery operations across multilingual wiki deployments with structured metadata and filtering capabilities.

    about

    WikiJS is a community-built MCP server published by ricardocenci that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with WikiJS to search, retrieve, and explore multilingual wiki content using advanced GraphQL-based operations It is categorized under analytics data, productivity.

    how to install

    You can install WikiJS in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

    license

    MIT

    WikiJS is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

    readme

    WikiJS MCP Server

    A Model Context Protocol (MCP) server that provides integration with WikiJS, allowing AI assistants to search and retrieve content from your WikiJS knowledge base.

    Overview

    This MCP server enables AI assistants to interact with WikiJS instances by providing tools to:

    • Search for pages by query string
    • Retrieve pages by ID
    • Retrieve pages by path and locale
    • Get all pages from the wiki

    Configuration for Cursor

    Stdio

    {
      "mcpServers": {
        "wikijs-mcp": {
          "command": "npx",
            "args": [
                "wikijs-mcp"
            ],
            "env": {
                "WIKIJS_URL": <your wikijs url>,
                "WIKIJS_API_KEY": <your wikijs api key>
            }
        }
      }
    }
    

    Streamable Http

    Host Machine

    Start the server TRANSPORT_METHOD=streamable-http TRANSPORT_OPTIONS_PORT=8080 npx wikijs-mcp (See Environment Variables for all available variables)

    IDE

    {
      "mcpServers": {
        "wikijs-mcp": {
          "transport": "http-streamable",
          "name": "WikiJS MCP",
          "url": <your mcp host url with port>/mcp
        }
      }
    }
    

    Getting a WikiJS API Key

    1. Log into your WikiJS instance as an administrator
    2. Go to Administration > API Access
    3. Create a new API key with appropriate permissions
    4. Copy the generated key to your .env file

    Development

    1. Clone the repository:
    git clone https://github.com/RicardoCenci/wikijs-mcp.git
    cd wikijs-mcp
    
    1. Install dependencies:
    npm install
    
    1. Copy the environment template and fill out its contents
    cp env.example .env
    
    1. Build the project If you have make installed:
    make build
    
    1. Deploy the WikiJS instance for testing
    docker compose up -d
    

    Usage

    npx wikijs-mcp
    

    Environment Variables

    VariableDescriptionRequiredAllowed ValuesDefault
    WIKIJS_URLURL of your WikiJS instanceYes--
    WIKIJS_API_KEYWikiJS API keyYes--
    TRANSPORT_METHODThe transport methodNostdio, streamable-httpstdio
    TRANSPORT_OPTIONS_CORS_ORIGINCors Origin (only on streamable-http)No-*
    TRANSPORT_OPTIONS_CORS_HEADERSCors Headers, comma separated (only on streamable-http)No-Content-Type=mcp-session-id
    TRANSPORT_OPTIONS_CORS_METHODSCors Methods, comma separated (only on streamable-http)No-GET,POST,OPTIONS
    TRANSPORT_OPTIONS_SESSION_TIMEOUT_MSSession timeout (only on streamable-http)No-60000

    License

    This project is licensed under the MIT License.

    FAQ

    What is the WikiJS MCP server?
    WikiJS is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
    How do MCP servers relate to agent skills?
    Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
    How are reviews shown for WikiJS?
    This profile displays 60 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

    Use Cases

    Extended AI Capabilities

    Add new capabilities to Claude beyond text generation

    Example

    Access external data sources, execute code, interact with tools and services

    Transform Claude from chatbot to action-taking agent

    Context Enhancement

    Provide Claude with access to relevant context and data

    Example

    Load project documentation, access knowledge bases, query databases

    Get more accurate, context-aware responses

    Workflow Automation

    Automate multi-step workflows combining AI and external tools

    Example

    Research → Summarize → Create document → Send notification

    Complete complex tasks end-to-end without manual steps

    Implementation Guide

    Prerequisites

    • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
    • Basic understanding of MCP architecture and capabilities
    • Access credentials for integrated services (if required)
    • Willingness to experiment and iterate on configuration

    Time Estimate

    15-60 minutes depending on server complexity

    Installation Steps

    1. 1.Install MCP server: npm install -g [package-name] or via GitHub
    2. 2.Add server configuration to ~/.claude/mcp.json
    3. 3.Provide required credentials and configuration
    4. 4.Restart Claude Desktop to load new server
    5. 5.Test basic functionality with simple prompts
    6. 6.Explore capabilities and experiment with use cases
    7. 7.Document successful patterns for reuse

    Troubleshooting

    • MCP server not loading: Check config syntax, verify installation
    • Connection errors: Check network, firewall, credentials
    • Feature not working: Read server docs, check required parameters
    • Performance issues: Monitor resource usage, check for network latency
    • Conflicts with other servers: Check port assignments, namespace collisions

    Best Practices

    ✓ Do

    • +Read server documentation thoroughly before setup
    • +Start with simple use cases to validate functionality
    • +Test in non-production environment first
    • +Monitor resource usage and performance
    • +Keep servers updated for bug fixes and new features
    • +Document configuration for team members
    • +Use environment variables for sensitive configuration

    ✗ Don't

    • Don't grant overly permissive access to MCP servers
    • Don't skip reading security considerations in docs
    • Don't expose sensitive data without proper controls
    • Don't run untrusted MCP servers without code review
    • Don't ignore error messages—investigate root cause

    💡 Pro Tips

    • Combine multiple MCP servers for powerful workflows
    • Create custom MCP servers for your specific needs
    • Share successful configurations with team
    • Use MCP inspector for debugging
    • Join MCP community for tips and troubleshooting

    Technical Details

    Architecture

    Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

    Protocols

    • Model Context Protocol (MCP)
    • JSON-RPC 2.0
    • stdio or HTTP transport

    Compatibility

    • Claude Desktop
    • Cursor IDE
    • Custom MCP clients

    When to Use This

    ✓ Use When

    Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

    ✗ Avoid When

    Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

    Integration

    • Tool composition: Chain multiple MCP tools in workflows
    • Context augmentation: Provide AI with relevant external data
    • Action delegation: Let AI execute tasks on external systems
    • Bidirectional sync: Keep AI context and external systems in sync

    Discussion

    Product Hunt–style comments (not star reviews)
    • No comments yet — start the thread.

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    Ratings

    4.660 reviews
    • Ishan Thomas· Dec 24, 2024

      WikiJS is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

    • Li Shah· Dec 12, 2024

      WikiJS is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

    • Fatima Singh· Dec 12, 2024

      WikiJS is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

    • Arjun Abbas· Dec 12, 2024

      We wired WikiJS into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

    • Dhruvi Jain· Dec 8, 2024

      We wired WikiJS into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

    • Evelyn Menon· Dec 8, 2024

      We evaluated WikiJS against two servers with overlapping tools; this profile had the clearer scope statement.

    • Oshnikdeep· Nov 27, 2024

      WikiJS is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

    • Evelyn Gupta· Nov 27, 2024

      WikiJS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

    • Arjun Rahman· Nov 19, 2024

      WikiJS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

    • Michael Bansal· Nov 15, 2024

      We wired WikiJS into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

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