Meilisearch MCP Server

enable-vector-search

Activate vector search functionality in Meilisearch to enable semantic similarity-based document retrieval.

Instructions

Enable the vector search experimental feature in Meilisearch

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Implementation Reference

src/tools/vector-tools.ts:25-37 (handler)

Handler function that enables the vector search experimental feature by posting to the Meilisearch /experimental-features endpoint with vectorStore: true, and returns the response or error.

  async () => {
    try {
      const response = await apiClient.post('/experimental-features', {
        vectorStore: true,
      });
      return {
        content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }],
      };
    } catch (error) {
      return createErrorResponse(error);
    }
  }
);

src/tools/vector-tools.ts:21-37 (registration)

Registers the enable-vector-search tool on the MCP server with no input schema and the inline handler function.

server.tool(
  "enable-vector-search",
  "Enable the vector search experimental feature in Meilisearch",
  {},
  async () => {
    try {
      const response = await apiClient.post('/experimental-features', {
        vectorStore: true,
      });
      return {
        content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }],
      };
    } catch (error) {
      return createErrorResponse(error);
    }
  }
);

src/index.ts:68-68 (registration)
Registers all vector tools, including enable-vector-search, by calling registerVectorTools on the main MCP server instance.
```
registerVectorTools(server);
```

Schema Changelog

Changes observed during successful MCP inspections.

First observedDec 10, 2025

TDQS

B3.4/5.0

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. It states the action ('Enable') but lacks behavioral details: it doesn't specify if this requires admin permissions, is irreversible, affects performance, has side effects, or returns confirmation. 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 that directly states the tool's purpose with zero wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 mutation operation enabling an experimental feature) and the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, effects, or response format, leaving the agent with insufficient 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.

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. A baseline of 4 is applied since there are no parameters to document, and the description doesn't add unnecessary details.

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 specific action ('Enable') and the target resource ('vector search experimental feature in Meilisearch'), distinguishing it from siblings like 'get-experimental-features' (which reads) or 'vector-search' (which uses the feature). It precisely communicates what the tool does without being tautological.

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 prerequisites (e.g., whether the feature must be available), exclusions, or related tools like 'get-experimental-features' for checking status. Usage is implied but not explicitly stated.

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

Deploy Server