Skip to main content
Glama
bigjeager

Bear App MCP Server

by bigjeager

bear_grab_url

Extract web page content to create notes in Bear App, enabling users to save online information directly into their note-taking workflow.

Instructions

Create a note from web page content

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to grab content from
tagsNoComma-separated list of tags
pinNoPin note to top of list
waitNoWait for content to load

Implementation Reference

  • src/index.ts:630-655 (registration)
    Registration of the 'bear_grab_url' tool in the ListTools response, including name, description, and input schema.
    {
      name: "bear_grab_url",
      description: "Create a note from web page content",
      inputSchema: {
        type: "object",
        properties: {
          url: {
            type: "string",
            description: "URL to grab content from"
          },
          tags: {
            type: "string",
            description: "Comma-separated list of tags"
          },
          pin: {
            type: "boolean",
            description: "Pin note to top of list"
          },
          wait: {
            type: "boolean",
            description: "Wait for content to load"
          }
        },
        required: ["url"]
      }
    },
  • src/index.ts:731-732 (registration)
    Dispatch/registration case in the CallToolRequestSchema switch statement that routes to the grabUrl handler.
    case "bear_grab_url":
      return await this.grabUrl(args);
  • The handler function 'grabUrl' that constructs Bear 'grab-url' parameters, executes via callback, and formats response with created note data.
    private async grabUrl(args: any) {
      const params: Record<string, string | boolean> = { url: args.url };
      
      if (args.tags) params.tags = args.tags;
      if (args.pin) params.pin = "yes";
      if (args.wait) params.wait = "yes";
    
      const grabData = await this.executeWithCallback("grab-url", params);
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify({
              message: `Created note from URL: ${args.url}`,
              note: grabData
            }, null, 2)
          }
        ]
      };
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'create' (implying a write operation) but doesn't specify permissions, rate limits, or what happens if the URL is invalid. It hints at web scraping ('grab content') but doesn't detail potential failures or side effects, leaving significant gaps for a tool that modifies data.

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 that front-loads the core functionality ('Create a note from web page content') with zero wasted words. It's appropriately sized for a straightforward tool, making it easy for an agent 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?

Given the complexity of a web scraping and note creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'grab content' entails (e.g., HTML parsing, error handling), the note's format, or return values, leaving the agent with critical unknowns for a mutation operation.

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?

The schema description coverage is 100%, so the schema already documents all four parameters (url, tags, pin, wait) with clear descriptions. The description adds no additional meaning beyond implying URL-based content extraction, which is already suggested by the tool name. This meets 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 ('Create a note') and resource ('from web page content'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'bear_create_note' or 'bear_add_text', which might also create notes, so it doesn't reach the highest score.

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 like 'bear_add_text' (for text content) or 'bear_create_note' (for manual note creation). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from the name 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/bigjeager/bear-mcp-server'

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