Azure Wiki Search MCP Server

What does “Azure Wiki Search” MCP Server do?

The Azure Wiki Search MCP Server implements the MCP (Model Context Protocol) specification to allow AI agents to search content on Azure wiki. Acting as a bridge between AI assistants and Azure wiki resources, this server enables powerful workflows where AI models can perform search queries and retrieve wiki documents programmatically. By exposing search and retrieval functionality, it helps developers and AI agents automate information gathering, documentation retrieval, and knowledge management within Azure DevOps wiki environments. This enhances development workflows by streamlining access to internal knowledge bases and documentation, making it easier for teams to surface relevant information through AI-driven tools.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

Ready to grow your business?

Start your free trial today and see results within days.

Request demo Log in

List of Resources

No explicit resources are listed in the documentation or code. The server’s focus appears to be on search and retrieval.

List of Tools

• search_wiki
  Search Edge Wiki to find related material for a specified query.

• get_wiki_by_path
  Retrieve wiki content by providing a specific path.

Join our newsletter

Get latest tips, trends, and deals for free.

Email address

Subscribe

Use Cases of this MCP Server

• Automated Knowledge Search
  Allows AI assistants and developers to programmatically search for relevant documentation or solutions within Azure wiki, reducing manual effort and improving productivity.

• Documentation Retrieval
  Enables retrieval of specific wiki pages or documentation sections, facilitating access to structured knowledge for onboarding, troubleshooting, or knowledge sharing.

• AI-Powered Support Bots
  Integrate with support or chatbots to automatically fetch and present wiki content in response to user queries.

• Project Knowledge Management
  Centralizes access to project-specific documentation, making it easier for teams to maintain and discover knowledge assets.

How to set it up

Windsurf

1. Install prerequisites: latest VS Code, GitHub Copilot extensions, Python 3.10+, and uv.

2. Clone the repository:
   git clone https://github.com/coder-linping/azure-wiki-search-server.git

3. Set up the environment with uv and activate the virtual environment.

4. Add the MCP server configuration to your User Settings (JSON) or .vscode/mcp.json:

   "mcp": {
     "servers": {
       "edge_wiki": {
         "command": "uv",
         "args": [
             "--directory",
             "<absolute path to your cloned folder>",
             "run",
             "src/edge_wiki.py"
         ],
         "env": {
             "PAT": "Your personal access token",
             "ORG": "Your organization，default is microsoft",
             "PROJECT": "Your project, default is Edge"
         }
       }
     }
   }
   

5. Save configuration, restart VS Code, and verify connection.

Claude

No specific instructions provided for Claude. Use similar JSON configuration as above in the platform’s MCP server settings.

Cursor

No specific instructions provided for Cursor. Use similar JSON configuration as above in the platform’s MCP server settings.

Cline

No specific instructions provided for Cline. Use similar JSON configuration as above in the platform’s MCP server settings.

Securing API Keys

• Use environment variables in the env section of your MCP configuration to store sensitive keys:

  "env": {
      "PAT": "Your personal access token",
      "ORG": "Your organization",
      "PROJECT": "Your project"
  }
  

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "azure-wiki-search": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “azure-wiki-search” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available documentation, Azure Wiki Search MCP Server is functional for basic wiki search and retrieval use cases, but lacks detailed resource and prompt templates, as well as broader platform-specific instructions. It scores as a minimal but usable MCP server.

MCP Score

Our opinion:
This MCP server provides basic search and retrieval features for Azure wiki, which is useful for targeted development workflows. However, lack of detailed resource and prompt support, platform-specific instructions, and community activity limit its flexibility and extensibility.
Rating: 4/10