Jekyll MCP Server
Indexes and searches Jekyll blog content, enabling AI assistants to search posts by keyword/category/tags, retrieve full post content, compare drafts against published posts, and analyze blog categories and tags.
README
Jekyll MCP Server
A Model Context Protocol (MCP) server that indexes and searches Jekyll blog content, enabling AI assistants like Claude to interact with your blog posts.
Features
- Index Jekyll blog posts and drafts with front matter parsing
- Search posts by keyword, category, or tags
- Retrieve full post content by slug
- Compare draft content against published posts to detect duplicates
- List all categories and tags with post counts
- Support for both Markdown (.md) and AsciiDoc (.adoc) formats
- Fast keyword-based search
Installation
Using uv (recommended)
uv pip install jekyll-mcp-server
Using pip
pip install jekyll-mcp-server
From source
git clone https://github.com/jottinger/jekyll-mcp-server.git
cd jekyll-mcp-server
uv pip install -e .
Configuration
The server needs to know where your Jekyll blog content is located. There are two ways to configure this:
Option 1: Environment Variables
Set these environment variables before running the server:
export JEKYLL_POSTS_DIR="/path/to/your/blog/_posts"
export JEKYLL_DRAFTS_DIR="/path/to/your/blog/_drafts" # Optional
Option 2: Run from Jekyll Project Directory
If you run the server from your Jekyll project root (where _posts and _drafts directories exist), it will automatically detect them.
Usage
With Claude Code
Add to your Claude Code MCP configuration:
{
"mcpServers": {
"jekyll-blog": {
"command": "jekyll-mcp-server",
"env": {
"JEKYLL_POSTS_DIR": "/path/to/your/blog/_posts",
"JEKYLL_DRAFTS_DIR": "/path/to/your/blog/_drafts"
}
}
}
}
Then restart Claude Code. The server will start automatically when needed.
Manual Launch
Create a launch script (see examples/launch-server.sh):
#!/bin/bash
export JEKYLL_POSTS_DIR="/path/to/your/blog/_posts"
export JEKYLL_DRAFTS_DIR="/path/to/your/blog/_drafts"
jekyll-mcp-server
Make it executable and run:
chmod +x launch-server.sh
./launch-server.sh
Available MCP Tools
Once connected, the server provides these tools to AI assistants:
search_posts
Search for blog posts by keyword, category, or tags.
Parameters:
query(string, optional): Search term to find in title, content, or slugcategory(string, optional): Filter by categorytags(string, optional): Comma-separated list of tagslimit(number, optional): Maximum results (default: 10)
Example:
Search for posts about "AI writing" in the "blog" category
get_post
Retrieve full content of a specific post by slug.
Parameters:
slug(string, required): The post slug
Example:
Get the post with slug "working-with-the-machine"
list_categories
List all blog categories with post counts.
Example:
Show me all categories
list_tags
List all blog tags with post counts.
Example:
What tags do I use?
compare_draft
Compare draft content against published posts to find similar content (helps avoid duplicate posts).
Parameters:
draft_content(string, required): The draft text to comparelimit(number, optional): Maximum similar posts to return (default: 5)
Example:
Compare this draft against my published posts:
[paste draft content]
Example Workflow
Here's how you might use this with Claude Code:
-
Before writing a new post:
Search my posts for "AI writing process" -
Check if you've covered a topic:
Have I written about MCP servers before? -
Prevent duplicate content:
Compare this draft against my published posts: [paste draft] -
Retrieve existing content:
Get the full content of my post "working-with-the-machine" -
Analyze your blog:
What categories do I write about most?
Reindexing Content
The server indexes content on startup. After publishing new posts or making significant changes:
- Stop the server (if running standalone)
- Restart it to refresh the index
With Claude Code, the server restarts automatically when needed.
Development
Setup
git clone https://github.com/jottinger/jekyll-mcp-server.git
cd jekyll-mcp-server
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e ".[dev]"
Running Tests
pytest
Project Structure
jekyll-mcp-server/
├── jekyll_mcp/
│ ├── __init__.py
│ ├── server.py # MCP server implementation
│ ├── indexer.py # Post indexing logic
│ ├── parser.py # Front matter parsing
│ └── tools.py # MCP tool implementations
├── examples/
│ ├── claude-code-config.json
│ └── launch-server.sh
├── tests/
├── LICENSE
├── README.md
└── pyproject.toml
Requirements
- Python 3.10 or higher
- Jekyll blog with standard
_postsdirectory structure - Posts with YAML front matter
License
MIT License - see LICENSE file for details.
Contributing
Contributions welcome! Please feel free to submit a Pull Request.
Acknowledgments
Built using the Model Context Protocol by Anthropic.
Created with assistance from Claude Code.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。