Bear App MCP – A Bridge Between AI Assistants and Your Notes

The Bear App MCP solves the common pain point of programmatically accessing a rich, markdown‑based note repository from an AI assistant. Bear is a popular writing app that stores notes locally in a structured format, but it offers no native API for external tools. By exposing a set of MCP tools, this server lets Claude or any other AI client read, filter, summarize, and delete notes directly from Bear without leaving the assistant’s workflow.

At its core, the server implements four straightforward yet powerful operations:

• Get List of Notes – Pulls the most recently updated notes, optionally limited to a specific count. The response includes each note’s title and last‑modified timestamp, giving the AI a quick snapshot of current content.
• Get Notes by Tag – Filters notes using Bear’s tagging system (tags must be prefixed with ). The tool returns all matching notes, sorted by update date, enabling the assistant to focus on a specific project or topic.
• Get Note Summary – Fetches the first five lines of a note’s body along with its timestamp. This lightweight preview is ideal for quick context checks or for generating concise summaries without downloading the entire document.
• Delete Note – Marks a note as trashed by title, allowing the AI to clean up obsolete or duplicated entries. A clear success/failure message confirms the action.

These capabilities are delivered through a simple Python implementation that can be launched via a single command in an MCP configuration file. The design keeps the interface minimal while still offering enough flexibility for real‑world use cases.

Why It Matters for Developers

Developers building AI‑powered note‑taking assistants or knowledge management tools can now treat Bear as a first‑class data source. The server’s operations integrate seamlessly into existing MCP workflows: an AI can query for the latest research notes, summarize a draft article, or purge outdated drafts—all without manual intervention. Because each tool returns structured JSON, the assistant can parse results instantly and chain them into more complex reasoning or generation tasks.

Use Cases

• Smart Research Assistant – Automatically retrieve the newest literature notes tagged with , summarize them, and embed insights into a report.
• Writing Workflow Automation – Pull draft outlines tagged , generate a concise preview, and delete drafts that have been published.
• Personal Knowledge Base Management – Keep the most relevant notes surfaced by querying tags like or , and clean up the archive with a single delete command.

Standout Features

• Tag‑based Filtering – Leverages Bear’s native tagging system for precise queries.
• Lightweight Summaries – Avoids full‑content transfers by returning only the first five lines, reducing latency.
• Safe Deletion – Notes are moved to Bear’s trash rather than permanently removed, preserving a safety net.
• Zero‑Dependency Runtime – Requires only Python 3.11 and the standard UV toolchain, keeping the deployment footprint small.

In short, the Bear App MCP turns a beloved note‑taking app into an AI‑friendly data source, enabling developers to build smarter, more integrated assistants that can read, summarize, and manage content on the fly.