MCP server implementation that enables AI assistants to search and reference Kibela content
概览
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. The mcp-kibela server provides the following features: - : Search Kibela notes by keywords - : Fetch your latest notes - : Get note content and comments by ID - : Get note content by path - : Create a new note - : Update note content by note id - Node.js (v18 or higher) - MCP Client (Claude Desktop, Cursor, etc.) - Kibela Access Token (How to get a token) - Git (if building from source) 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) 1. Use npm run build:watch to build the project in watch mode. 2. Use npx @modelcontextprotocol/inspector to inspect the MCP server.
README
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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
{
"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
{
"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
{
"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"
}
}
}
}
安装
docker run -i --rm -e KIBELA_TEAM -e KIBELA_TOKEN ghcr.io/kj455/mcp-kibela:latest配置
{
"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"
}
}
}
}