Skip to main content
Glama
MCP-Mirror
by MCP-Mirror

search_notes

Find specific notes in Joplin by entering search terms, with options to limit results for focused discovery.

Instructions

Search for notes in Joplin.

Args:
    args: Search parameters
        query: Search query string
        limit: Maximum number of results (default: 100)

Returns:
    Dictionary containing search results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool returns a 'Dictionary containing search results', it doesn't specify what that dictionary contains (e.g., note IDs, titles, content snippets), whether results are paginated, or any performance considerations like rate limits. For a search tool with zero annotation coverage, this leaves critical behavioral traits unclear.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with the core purpose. The Args and Returns sections are structured clearly, though the 'args' parameter could be more directly explained. There's minimal waste, but the nested parameter explanation could be slightly more concise.

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 tool's complexity (search functionality with parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return value structure, error handling, or how results are ordered/filtered. For a tool that likely returns multiple results, this leaves too much ambiguity for effective use.

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 description adds some parameter semantics beyond the input schema, which has 0% description coverage. It explains that 'args' contains 'Search parameters' and details 'query' as a 'Search query string' and 'limit' with a default of 100. However, it doesn't clarify the query syntax (e.g., wildcards, operators) or what 'limit' applies to (e.g., per page, total results), leaving gaps in understanding.

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 tool's purpose: 'Search for notes in Joplin.' This specifies the verb ('Search') and resource ('notes in Joplin'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_note' or 'import_markdown', which prevents a perfect 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. It doesn't mention scenarios where search is preferable over 'get_note' for retrieving specific notes or how it complements other tools like 'create_note' or 'update_note'. This lack of contextual usage advice is a significant gap.

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/MCP-Mirror/dweigend_joplin-mcp-server'

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