Skip to main content
Glama
devlimelabs

Meilisearch MCP Server

by devlimelabs

reset-faceting

Reset faceting settings to default values for a Meilisearch index. Use this tool to clear custom facet configurations and restore original search filtering behavior.

Instructions

Reset the faceting setting to its default value

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexUidYesUnique identifier of the index

Implementation Reference

  • Handler function that executes the reset-faceting tool by sending a DELETE request to /indexes/{indexUid}/settings/faceting via apiClient.
        try {
          const response = await apiClient.delete(`/indexes/${indexUid}/settings/${endpoint}`);
          return {
            content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }],
          };
        } catch (error) {
          return createErrorResponse(error);
        }
      }
    );
  • Zod input schema for the reset-faceting tool, requiring an indexUid string parameter.
      indexUid: z.string().describe("Unique identifier of the index"),
    },
    async ({ indexUid }) => {
  • forEach loop that dynamically registers the reset-faceting tool (and others) using server.tool() with the shared schema and handler.
    resetSettingsTools.forEach(({ name, endpoint, description }) => {
      server.tool(
        name,
        description,
        {
          indexUid: z.string().describe("Unique identifier of the index"),
        },
        async ({ indexUid }) => {
          try {
            const response = await apiClient.delete(`/indexes/${indexUid}/settings/${endpoint}`);
            return {
              content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }],
            };
          } catch (error) {
            return createErrorResponse(error);
          }
        }
      );
    });
  • Specific configuration object in resetSettingsTools array that triggers registration of the 'reset-faceting' tool with endpoint 'faceting'.
    {
      name: "reset-faceting",
      endpoint: "faceting",
      description: "Reset the faceting setting to its default value",
    },
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action ('reset') which implies a mutation, but doesn't disclose behavioral traits such as whether this is destructive (likely yes, as it changes settings), requires specific permissions, has side effects on search results, or provides confirmation output. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence with zero waste—it directly states the action and outcome. It's appropriately sized for a simple tool and front-loaded with the key information.

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 is a mutation (reset) with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., impact, permissions), doesn't explain the return value or confirmation, and relies solely on the schema for parameters. For a tool that modifies settings, this leaves significant gaps for an AI agent.

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%, with one parameter 'indexUid' fully documented in the schema. The description doesn't add any meaning beyond the schema (e.g., it doesn't explain what 'faceting' is or how the reset applies). Baseline is 3 since the schema does the heavy lifting, but no extra value is provided.

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 action ('reset') and the resource ('faceting setting'), specifying it sets to the default value. It distinguishes from siblings like 'update-faceting' (which modifies) and 'get-faceting' (which retrieves), but doesn't explicitly mention the index context, which is implied by the parameter. This is clear but could be slightly more specific about the scope.

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?

No explicit guidance on when to use this tool versus alternatives like 'update-faceting' or 'get-faceting'. The description implies it's for resetting to defaults, but doesn't state prerequisites (e.g., after custom changes) or exclusions (e.g., not for initial setup). Usage is implied from the action, but lacks contextual direction.

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/devlimelabs/meilisearch-ts-mcp'

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