Mowen MCP Server Overview

Mowen MCP Server bridges the gap between AI assistants and the 墨问笔记 knowledge‑base by implementing the Model Context Protocol (MCP). It allows tools such as Cursor, Claude Desktop, or any MCP‑compatible client to create, edit, and manage notes directly within the AI workflow. By exposing a unified rich‑text API, developers can treat note operations as first‑class actions in conversational agents, enabling context‑aware knowledge retrieval and incremental content generation.

The server solves the practical problem of context leakage when an AI assistant needs to persist or reference user knowledge. Traditional approaches require manual copying or separate web interfaces, breaking the conversational flow and increasing cognitive load. Mowen MCP Server eliminates this friction: an assistant can issue a or command, and the server translates it into a call to the native 墨问 API. Because all note content is expressed in a consistent rich‑text format—paragraphs, quotes, embedded files, and internal links—the assistant can compose complex documents while the server handles serialization, permission checks, and file uploads.

Key capabilities include:

• Rich‑text note creation and replacement: Paragraphs can contain bold, highlight, link, or custom metadata; quotes and internal note links create a navigable knowledge graph.
• File uploads: Images, audio, and PDF files can be attached from local paths or remote URLs. The server ensures absolute paths are used for local files, while URLs bypass path restrictions.
• Privacy controls: Each note can be set to public, private, or rule‑based visibility, giving developers fine‑grained access management.
• API key lifecycle: Users can reset or rotate their MOWEN API keys directly through the MCP interface, simplifying credential management.
• Unified interface: All operations share a single request schema, reducing the learning curve for developers integrating with multiple MCP tools.

In real‑world scenarios, a developer building an AI‑driven research assistant can let the model pull recent literature from 墨问, generate summaries, and automatically create a structured note with embedded PDFs. A team collaboration bot might capture meeting minutes, attach voice recordings, and link related project notes—all without leaving the chat. Because the server is lightweight (a single executable on Windows or a Python module), it can be deployed locally or in CI pipelines, ensuring data stays within the organization’s infrastructure.

By integrating Mowen MCP Server into AI workflows, developers gain a powerful, protocol‑compliant channel to persist and manipulate knowledge. The result is a seamless conversational experience where the assistant not only talks but also writes, stores, and organizes content in the same ecosystem that users already trust.