About Bear MCP Server
Bear MCP Server is an MCP server that gives access to Bear notes. It runs SQL commands against Bear's SQLite database, so AI clients can read and search notes.
Key features
- 01Read notes
- 02Search notes by text
- 03List all tags
Use cases
- 01Querying Bear notes from Claude Desktop
- 02Finding older notes by keyword
- 03Reviewing the tags used in Bear
MCP support
The server exposes the get_notes, get_tags and get_notes_like tools to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEBear MCP Server
This project is a Model Context Protocol (MCP) server that provides access to the Bear Notes.
Bear stores notes on SQLite database. This MCP server runs some SQL commands to access this notes. https://bear.app/faq/where-are-bears-notes-located

Features
- Read notes
- Search notes by text
- List all tags
Installation
# Clone the project
git clone https://github.com/akseyh/bear-mcp-server
# Change directory
cd bear-mcp-server
# Install dependencies
npm install
# Build the project
npm run build
Claude Desktop Config
Update your claude_desktop_config.json
Docker
{
"mcpServers": {
"bear": {
"command": "docker",
"args": [
"run",
"-v",
"/Users/[YOUR_USER_NAME]/Library/Group Containers/9K33E3U3T4.net.shinyfrog.bear/Application Data:/app/db",
"-i",
"akseyh/bear-mcp-server"
]
}
}
}
NPM
{
"mcpServers": {
"bear": {
"command": "npx",
"args": [
"bear-mcp-server"
]
}
}
}
When the server is started, the following MCP tools become available:
get_notes: Retrieves all notesget_tags: Lists all tagsget_notes_like: Searches for notes containing specific text
Requirements
- Node.js
- Bear note application (macOS)
- Access to Bear database
License
ISC
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
