Skip to main content
Glama
bborbe

Semantic Search MCP

by bborbe

search_related

Find notes semantically related to your query text, ranked by meaning so you can locate relevant content and detect duplicates before adding new notes.

Instructions

Search for notes semantically related to the query text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe text to search for
top_kNoNumber of results to return (default 5)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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 adds the key trait that the search is semantic (not lexical), but it does not explicitly state whether the operation is read-only or if there are any side effects. The word 'search' implies safety, but this is not confirmed.

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, clear sentence with no redundant words. It is front-loaded with the action and directly conveys the core functionality, making it highly concise and well-structured.

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

Completeness4/5

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

For a simple search tool with full schema coverage and an output schema present, the description is largely complete. It explains the main purpose and semantically relevant behavior. However, it lacks explicit usage guidance and does not confirm the read-only nature in the absence of annotations, leaving minor gaps.

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 coverage is 100%: both 'query' and 'top_k' have descriptions in the input schema. The description does not add any additional parameter semantics beyond what is already in the schema, so the baseline score of 3 applies.

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 tool searches for notes semantically related to the query text. It specifies a concrete action (search), the resource (notes), and the nature (semantic relatedness), which effectively distinguishes it from sibling tools like check_duplicates and get_content.

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

Usage Guidelines3/5

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

The description implies usage (when you need semantically related notes) but does not explicitly mention alternatives or exclusions. No guidance is given on when to choose this tool over check_duplicates or get_content, though the semantic focus provides some context.

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/bborbe/semantic-search'

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