MCP Prompt Manager

by Tae4an

Overview Schema Source Related Servers Discussions Admin

JavaScript

Local

search-prompts

Search prompts by filename or content using fuzzy matching that handles typos and partial inputs.

Instructions

Search prompts by filename or content with intelligent fuzzy matching

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search-prompts"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	Search query (supports typos and partial matches)
`threshold`	No	Similarity threshold (0-1, lower = more permissive, default: 0.3)
`maxResults`	No	Maximum number of results (default: 10)
`searchInMeta`	No	Whether to search in metadata (tags, category) (default: true)
`searchInContent`	No	Whether to search in prompt content (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 30, 2026

TDQS

A3.6/5.0

Behavior2/5

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

No annotations are provided, so the description fully carries the burden of behavioral disclosure. It only mentions 'intelligent fuzzy matching' without explaining how matching works, default behavior, rate limits, or side effects. For a search tool with no annotations, this is insufficient.

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 sentence, concise and to the point. Every word is useful, no fluff. It front-loads the key action and resource.

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 5 parameters, no output schema, and no annotations, the description should provide more context about return format, pagination, or order. It only hints at matching behavior. The tool is under-described for the complexity.

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 baseline is 3. The tool description does not add additional meaning beyond the schema; it only repeats the concept of fuzzy matching. No extra value is provided for parameter understanding.

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

Purpose5/5

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

The description clearly states the verb 'Search', the resource 'prompts', and specifies that it searches by 'filename or content' with 'intelligent fuzzy matching'. This distinguishes it from siblings like 'list-prompts' (which likely lists all prompts) and 'search-templates' (different resource).

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

Usage Guidelines4/5

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

The description implies use when you need fuzzy matching over filename or content, but it does not explicitly state when to use this tool versus alternatives like 'list-prompts' or 'search-templates'. The context from the purpose provides some guidance, but lack of explicit when-not-to-use or exclusion conditions prevents a 5.

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