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avarant

Typesense MCP Server

search

Search within a specific collection using keywords, filter, sort, group, or facet results to refine queries. Retrieve documents based on defined criteria and paginate results for efficient data access in Typesense databases.

Instructions

Performs a keyword search on a specific collection.

Args:
    ctx (Context): The MCP context.
    collection_name (str): The name of the collection to search within.
    query (str): The search query string. Use '*' for all documents.
    query_by (str): Comma-separated list of fields to search in.
    filter_by (str | None): Filter conditions (e.g., 'price:>100 && category:Electronics'). Defaults to None.
    sort_by (str | None): Sorting criteria (e.g., 'price:asc, rating:desc'). Defaults to None.
    group_by (str | None): Field to group results by. Defaults to None.
    facet_by (str | None): Fields to facet on. Defaults to None.
    per_page (int): Number of results per page. Defaults to 20.
    page (int): Page number to retrieve. Defaults to 1.


Returns:
    dict | str: The search results dictionary from Typesense or an error message string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_nameYes
facet_byNo
filter_byNo
group_byNo
pageNo
per_pageNo
queryYes
query_byYes
sort_byNo
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool 'Performs a keyword search' and describes parameters, it doesn't disclose important behavioral traits: whether this is a read-only operation, potential rate limits, authentication requirements, error handling patterns, or what happens with large result sets. The Returns section mentions 'error message string' but doesn't elaborate on failure modes.

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 well-structured with clear sections (Args, Returns) and front-loaded purpose. Every sentence earns its place by either stating the tool's purpose or documenting parameters. However, the parameter documentation is quite lengthy (9 parameters with examples), which is necessary given the complexity but reduces overall conciseness. The structure is logical but could be more compact.

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

Completeness3/5

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

Given the tool's complexity (9 parameters, no annotations, no output schema), the description is partially complete. It excels at parameter documentation but lacks behavioral context and usage guidelines. The Returns section mentions the format but doesn't describe the structure of successful results. For a search tool with many configuration options and no annotations, more behavioral disclosure would be beneficial.

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

Parameters5/5

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

The description provides excellent parameter semantics beyond the input schema. With 0% schema description coverage, the description fully compensates by explaining all 9 parameters with clear examples: 'Use '*' for all documents', 'e.g., 'price:>100 && category:Electronics'', 'e.g., 'price:asc, rating:desc'', and default values. This adds crucial meaning about how to format complex parameters like filter_by, sort_by, and facet_by.

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 'Performs a keyword search on a specific collection' which provides a specific verb ('search') and resource ('collection'). It distinguishes from siblings like 'vector_search' by specifying 'keyword search' and from CRUD operations like 'create_document' by focusing on retrieval. However, it doesn't explicitly differentiate from 'list_collections' or 'describe_collection' in terms of search vs listing.

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 when to choose 'search' over 'vector_search' (a key sibling), nor does it provide context about when keyword search is appropriate versus other operations like 'list_collections' or 'describe_collection'. The agent receives no usage boundaries or prerequisites.

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

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