mcp-kibela

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MCP server implementation that enables AI assistants to search and reference Kibela content

12 stars TypeScriptAI & Machine Learning Updated May 1, 2025

Documentation

mcp-kibela 🗒️

A Model Context Protocol (MCP) server implementation that enables AI assistants to search and reference Kibela content. This setup allows AI models like Claude to securely access information stored in Kibela.

Features 🚀

The mcp-kibela server provides the following features:

Note Search: Search Kibela notes by keywords
My Notes: Fetch your latest notes
Note Content: Get note content and comments by ID
Note by Path: Get note content by path
Create Note: Create a new note
Update Note Content: Update note content by note id

Prerequisites 📋

Before you begin, ensure you have:

Node.js (v18 or higher)
MCP Client (Claude Desktop, Cursor, etc.)
Kibela Access Token (How to get a token)
Git (if building from source)

Installation 🛠️

Usage with Cursor

json

{
  "kibela": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "--rm",
      "-e",
      "KIBELA_TEAM",
      "-e",
      "KIBELA_TOKEN",
      "ghcr.io/kj455/mcp-kibela:latest"
    ],
    "env": {
      "KIBELA_TEAM": "your-team-name from https://[team-name].kibe.la",
      "KIBELA_TOKEN": "your-token"
    }
  }
}

Usage with VSCode

json

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "kibela_team",
        "description": "Kibela team name",
        "password": false
      },
      {
        "type": "promptString",
        "id": "kibela_token",
        "description": "Kibela token",
        "password": true
      },
    ],
    "servers": {
      "kibela": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "-e",
          "KIBELA_TEAM",
          "-e",
          "KIBELA_TOKEN",
          "ghcr.io/kj455/mcp-kibela:latest"
        ],
        "env": {
          "KIBELA_TEAM": "${input:kibela_team}",
          "KIBELA_TOKEN": "${input:kibela_token}"
        }
      }
    }
  }
}

Usage with Claude Desktop

json

{
  "mcpServers": {
    "mcp-kibela": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "KIBELA_TEAM",
        "-e",
        "KIBELA_TOKEN",
        "ghcr.io/kj455/mcp-kibela:latest"
      ],
      "env": {
        "KIBELA_TEAM": "your-team-name from https://[team-name].kibe.la",
        "KIBELA_TOKEN": "your-token"
      }
    }
  }
}

Using Smithery

bash

npx -y @smithery/cli install @kj455/mcp-kibela --client claude

Environment Variables

The following environment variables are required:

`KIBELA_TEAM`: Your Kibela team name (required). You can find it from the URL of your Kibela team page. e.g. https://[team-name].kibe.la
`KIBELA_TOKEN`: Your Kibela API token (required)

Contributing

Any contributions are welcome!

Development

1. Use `npm run build:watch` to build the project in watch mode.

bash

npm run build:watch

2. Use `npx @modelcontextprotocol/inspector` to inspect the MCP server.

bash

npx @modelcontextprotocol/inspector node /path/to/mcp-kibela/dist/index.js

License 📄

MIT

Frequently asked questions

What is mcp-kibela?

mcp-kibela is MCP server implementation that enables AI assistants to search and reference Kibela content

How do I install mcp-kibela?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is mcp-kibela open source?

Yes — it is hosted on GitHub at https://github.com/kj455/mcp-kibela and has 12 stars.

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