Skip to main content
Glama

add_text

Add text to existing notes in Bear Notes by appending, prepending, or replacing content using note identifiers and text input.

Instructions

Add text to an existing note

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYesThe unique identifier of the note (ZUNIQUEIDENTIFIER)
textYesText to add
modeNoWhere to add textappend
open_noteNoOpen the note in Bear after modification

Implementation Reference

  • The actual implementation of the add_text function which constructs the URL for the Bear x-callback-url.
    def add_text(
        note_id: str,
        text: str,
        mode: str = "append",
        open_note: bool = False
    ) -> dict[str, str]:
        """
        Add text to an existing note.
    
        Args:
            note_id: The unique identifier of the note (ZUNIQUEIDENTIFIER)
            text: Text to add
            mode: Where to add text - "append", "prepend", or "replace"
            open_note: Open the note in Bear after modification
    
        Returns:
            Dictionary with operation result
        """
        if mode not in ["append", "prepend", "replace"]:
            return {"success": False, "error": f"Invalid mode: {mode}. Use append, prepend, or replace"}
    
        params = {
            "id": note_id,
            "text": text,
            "mode": mode
        }
    
        if open_note:
            params["open_note"] = "yes"
  • The MCP tool registration for 'add_text', including its input schema.
    Tool(
        name="add_text",
        description="Add text to an existing note",
        inputSchema={
            "type": "object",
            "properties": {
                "note_id": {
                    "type": "string",
                    "description": "The unique identifier of the note (ZUNIQUEIDENTIFIER)",
                },
                "text": {
                    "type": "string",
                    "description": "Text to add",
                },
                "mode": {
                    "type": "string",
                    "enum": ["append", "prepend", "replace"],
                    "description": "Where to add text",
                    "default": "append",
  • The MCP tool handler that parses arguments and calls the underlying add_text function.
    elif name == "add_text":
        if not isinstance(arguments, dict) or "note_id" not in arguments or "text" not in arguments:
            raise ValueError("Missing required arguments: note_id and text")
    
        result = add_text(
            note_id=arguments["note_id"],
            text=arguments["text"],
            mode=arguments.get("mode", "append"),
            open_note=arguments.get("open_note", False)
        )
        return [TextContent(type="text", text=str(result))]
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Add text' implies a mutation (not read-only), it lacks critical details: whether this requires specific permissions, if changes are reversible, potential side effects (e.g., modifying timestamps), or error conditions (e.g., invalid note_id). The description is minimal and doesn't compensate for the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Add text to an existing note') without unnecessary elaboration. Every word earns its place, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens on success (e.g., returns updated content?), error handling, or behavioral nuances like the 'mode' parameter's effect on existing text. Given the complexity of modifying resources, more context is needed to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are well-documented in the schema itself. The description adds no additional meaning about parameters beyond implying 'note_id' and 'text' are involved. It doesn't explain parameter interactions or provide context beyond what the schema already specifies, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Add text') and target resource ('to an existing note'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_note' (which creates new notes) or 'open_note' (which opens without modification), leaving some ambiguity about when this specific tool is appropriate versus alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing note), exclusions (e.g., not for creating new notes), or comparisons to siblings like 'create_note' for new notes or 'open_note' for viewing without modification. The agent must infer usage from context alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/maxim-ist/mcp-bear'

If you have feedback or need assistance with the MCP directory API, please join our Discord server