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Algolia Search MCP Server

by chick-p
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
JavaScript
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Algolia Search MCP Server

This repository have been archived. The Official server is released at Algolia Node.js MCP.

Features

  • Search for any text in your Algolia index

Related MCP server: Algolia

Setup

This package is installed as local.

  1. Clone the repository

  2. Install dependencies

    cd algolia-search-mcp-server
pnpm install

  3. Build the project and install it globally

    pnpm build
npm install -g .

  4. Configure your IDE:

    • cline(cline_mcp_settings.json)

      {
  "mcpServers": {
    "algolia-search-server": {
      "command": "algolia-search-server",
      "env": {
        "ALGOLIA_APPLICATION_ID": "<YOUR_ALGOLIA_APPLICATION_ID>",
        "ALGOLIA_SEARCH_API_KEY": "<YOUR_ALGOLIA_SEARCH_API_KEY>",
        "ALGOLIA_INDEX_NAME": "<YOUR_ALGOLIA_INDEX_NAME>"
      }
    }
  }
}

    • Visual Studio Code(settings.json)

      {
  "chat.mcp.discovery.enabled": true,
  "mcp": {
      "servers": {
          "algolia-search-server: {
              "command": "algolia-search-server",
              "env": {
                "ALGOLIA_APPLICATION_ID": "<YOUR_ALGOLIA_APPLICATION_ID>",
                "ALGOLIA_SEARCH_API_KEY": "<YOUR_ALGOLIA_SEARCH_API_KEY>",
                "ALGOLIA_INDEX_NAME": "<YOUR_ALGOLIA_INDEX_NAME>"
              }
          }
      }
  }
}

Available Tools

1 tool
search_indexC

Search query from Algolia index

ParametersJSON Schema
NameRequiredDescriptionDefault
qNoQuery string

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Search query') without detailing traits like read-only vs. destructive nature, authentication needs, rate limits, or response format. This leaves significant gaps in understanding the tool's behavior.

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 a single, efficient sentence with no wasted words, making it appropriately sized and front-loaded. However, it could be more structured by including key details, but it earns a high score for brevity and clarity within its limited scope.

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 (a search function with no output schema and no annotations), the description is incomplete. It lacks information on what the search returns, error handling, or any behavioral context, making it insufficient for an agent to fully understand how to use the tool effectively.

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 input schema has 100% description coverage, with the parameter 'q' documented as 'Query string'. The description adds no additional meaning beyond this, such as query syntax or examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.

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

Purpose3/5

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

The description 'Search query from Algolia index' specifies the action ('Search query') and target ('Algolia index'), which provides a basic purpose. However, it's vague about what exactly is being searched (e.g., documents, records, products) and doesn't distinguish from siblings since there are none, but it lacks specificity in the verb+resource combination.

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 offers no guidance on when to use this tool, such as scenarios, prerequisites, or alternatives. With no sibling tools, it doesn't need to differentiate, but it fails to provide any usage context, leaving the agent without direction on appropriate invocation.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev0.0.1
    • First observedsearch_index
Install Server
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TDQS

C2.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'search_index' has a clearly distinct purpose that cannot be confused with any other tool in this set.

Naming Consistency5/5

The naming is trivially consistent as there is only one tool. It follows a clear verb_noun pattern ('search_index'), and there are no other tools to create inconsistency or mixed conventions.

Tool Count2/5

A single tool is too few for a server named 'Algolia Search MCP Server', which implies broader search capabilities. While the tool 'search_index' covers basic search, typical search servers include tools for indexing, configuration, or multiple search methods, making this scope feel thin and incomplete.

Completeness2/5

The server is severely incomplete for a search domain. It only provides search functionality without any tools for creating, updating, or managing indices, or handling other search-related operations like analytics or settings. This creates significant gaps that will limit agent effectiveness.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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