Tinderbox MCP Server

The Tinderbox MCP Server bridges the gap between conversational AI assistants and Tinderbox, a macOS‑centric knowledge‑management system. By exposing a set of AppleScript‑backed tools over the Model Context Protocol, it lets an assistant such as Claude create, read, and manipulate notes inside a Tinderbox document using natural language. This removes the need for manual scripting or GUI interaction, enabling developers to embed structured knowledge work directly into AI‑driven workflows.

What Problem Does It Solve?

Tinderbox is powerful for organizing ideas, research notes, and complex hierarchies, but its primary interface is a desktop application with limited programmatic access. Developers often need to query or update notes from external services, automate repetitive tasks, or integrate Tinderbox data with other tools. The MCP server turns these manual interactions into declarative commands that an AI can issue, allowing a single conversation to orchestrate data entry, link generation, and hierarchical navigation across multiple documents.

Core Capabilities

The server offers a focused set of operations that cover the most common editing patterns:

• Create, read, and update notes – , , and let the assistant add new entries, fetch titles/text, or modify attributes such as position and color.
• Link management – creates connections between existing notes, while retrieves outgoing relationships.
• Hierarchy traversal – , , and related tools expose the document tree, enabling the assistant to explore or restructure nested content.
• Contextual awareness – Each tool requires a document reference, defaulting to “Playground” but easily configurable, so the assistant can target any open Tinderbox file.

These actions are thin wrappers around AppleScript commands, ensuring that changes happen instantly on the host machine without exposing raw scripts to the model.

Real‑World Use Cases

• Research synthesis – An assistant can scan a conversation, identify key points, and automatically generate notes in a research document, linking related ideas for quick navigation.
• Diagram generation – By setting / and attributes, the assistant can layout visual maps that mirror uploaded images or conceptual diagrams.
• Data migration – Bulk import of notes from other formats (e.g., Markdown or CSV) can be scripted through the MCP, preserving structure and metadata.
• Knowledge base maintenance – Periodic audits or updates of note attributes (e.g., tags, dates) can be scheduled via the assistant without manual editing.

Integration with AI Workflows

Because MCP servers are first‑class citizens in many AI platforms, the Tinderbox server can be added to a client’s configuration with a single JSON entry. Once registered, the assistant automatically learns about the available tools and can reference them in prompts. Developers can then craft higher‑level workflows—such as “summarize the meeting, create a note for each action item, and link them to the project plan”—and let the assistant handle all underlying document manipulations.

Unique Advantages

• Seamless macOS integration – Leveraging AppleScript ensures native performance and reliability, avoiding the overhead of third‑party APIs.
• Safety controls – The server’s tool descriptions warn about destructive operations, and developers can easily remove or disable risky tools (e.g., ) to safeguard data.
• Extensibility – The lightweight command list can be expanded with custom AppleScripts, allowing teams to tailor the server to niche workflows without rewriting core logic.

In summary, the Tinderbox MCP Server turns a desktop knowledge‑management application into an AI‑friendly API, empowering developers to automate complex note operations, weave structured data into conversational agents, and streamline research or project workflows—all through natural language.