Skip to main content
Glama

flexible_search

Execute FlexibleSearch queries to retrieve data from SAP Commerce Cloud (Hybris) databases using FlexibleSearch syntax for product, order, and system data management.

Instructions

Execute a FlexibleSearch query against the Hybris database. Use FlexibleSearch syntax.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFlexibleSearch query (e.g., "SELECT {pk}, {code} FROM {Product}")
maxCountNoMaximum number of results (default: 100)

Implementation Reference

  • The actual implementation of the executeFlexibleSearch logic which makes the API call to the Hybris HAC console.
    async executeFlexibleSearch(query: string, maxCount = 100): Promise<FlexibleSearchResult> {
      const formData = new URLSearchParams({
        flexibleSearchQuery: query,
        maxCount: maxCount.toString(),
      });
    
      return this.hacRequest<FlexibleSearchResult>(
        `${this.hacPrefix}/console/flexsearch/execute`,
        {
          method: 'POST',
          headers: {
            'Content-Type': 'application/x-www-form-urlencoded',
          },
          body: formData,
        }
      );
    }
  • MCP tool definition and input schema for flexible_search.
    {
      name: 'flexible_search',
      description: 'Execute a FlexibleSearch query against the Hybris database. Use FlexibleSearch syntax.',
      inputSchema: {
        type: 'object',
        properties: {
          query: {
            type: 'string',
            description: 'FlexibleSearch query (e.g., "SELECT {pk}, {code} FROM {Product}")',
          },
          maxCount: {
            type: 'number',
            description: 'Maximum number of results (default: 100)',
          },
        },
        required: ['query'],
      },
  • src/index.ts:416-421 (registration)
    The handler switch-case that dispatches the tool call to the Hybris client implementation.
    case 'flexible_search':
      result = await hybrisClient.executeFlexibleSearch(
        validateString(args, 'query', true),
        validateNumber(args, 'maxCount', { min: 1, max: 10000 })
      );
      break;
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. It mentions the query syntax but doesn't cover critical aspects like permissions needed, whether this is read-only or can modify data, rate limits, error handling, or what the output looks like. For a database query tool with zero annotation coverage, this leaves significant gaps.

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 extremely concise with just two sentences that directly state the tool's purpose and required syntax. Every word earns its place with zero wasted content.

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?

For a database query tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, what errors might occur, security implications, or how it differs from sibling query tools. The agent would struggle to use this effectively without trial and error.

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%, so the schema already fully documents both parameters. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high schema coverage but not providing extra value.

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 ('Execute a FlexibleSearch query') and target resource ('against the Hybris database'), with specific syntax mentioned. However, it doesn't distinguish this from sibling tools like 'search_products' or 'execute_groovy' that might also query the database.

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 guidance is provided on when to use this tool versus alternatives like 'search_products' or 'execute_groovy'. The description only states what the tool does, not when it's appropriate or what its limitations are relative to siblings.

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/mcieunic/hybris-mcp-main'

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