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Meilisearch MCP Server

by devlimelabs

reset-ranking-rules

Restore default ranking rules for a Meilisearch index to reset search result ordering to standard configuration.

Instructions

Reset the ranking rules setting to its default value

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexUidYesUnique identifier of the index

Implementation Reference

  • Handler function that performs a DELETE request to reset the ranking-rules setting for the specified index using the apiClient. Uses the endpoint 'ranking-rules' from the tool configuration. Returns the API response or handles errors with createErrorResponse.
    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);
      }
    }
  • Zod schema defining the input parameter 'indexUid' as a required string for identifying the Meilisearch index.
    {
      indexUid: z.string().describe("Unique identifier of the index"),
    },
  • Configuration object in resetSettingsTools array that defines the 'reset-ranking-rules' tool's name, endpoint ('ranking-rules'), and description. This is used in the forEach loop to register the tool with server.tool().
    {
      name: "reset-ranking-rules",
      endpoint: "ranking-rules",
      description: "Reset the ranking rules setting to its default value",
    },
  • The forEach loop that iterates over resetSettingsTools (including reset-ranking-rules) and registers each tool on the MCP server using server.tool(name, description, schema, 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);
          }
        }
      );
    });
  • src/index.ts:67-67 (registration)
    Top-level call to registerSettingsTools(server) in the main MCP server setup, which triggers the registration of the reset-ranking-rules tool.
    registerSettingsTools(server);
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. It implies a mutation ('reset'), but doesn't disclose behavioral traits like whether this requires specific permissions, if it's reversible, what the default value is, or potential side effects. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core action without unnecessary elaboration.

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 complexity of a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on what the reset entails (e.g., what the default ranking rules are), the outcome, or error conditions, leaving the agent with incomplete context for safe and effective use.

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 'indexUid' clearly documented as the 'Unique identifier of the index'. The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.

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 target ('ranking rules setting to its default value'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'update-ranking-rules' or other reset tools (e.g., 'reset-settings'), which would require explicit comparison to achieve a score of 5.

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 such as 'update-ranking-rules' or 'get-ranking-rules', nor does it mention prerequisites or context for resetting. This lack of explicit usage instructions limits its effectiveness for an AI agent.

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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