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ConsignCloud MCP Server

by modellers

search_suggest

Find accounts and items in ConsignCloud using full-text search across titles, descriptions, names, emails, and SKUs to retrieve detailed entity information.

Instructions

Search across accounts and items using full-text search. Returns matching entities with their full details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (searches titles, descriptions, names, emails, SKUs, etc.)
typesNoEntity types to search. Options: "items", "accounts". Leave empty to search both.

Implementation Reference

  • Handler for the search_suggest MCP tool. Extracts parameters and calls client.search, returning JSON-formatted results.
    case 'search_suggest':
      const { query, types } = args as any;
      return { content: [{ type: 'text', text: JSON.stringify(await client.search(query, types), null, 2) }] };
  • src/server.ts:238-253 (registration)
    Registers the search_suggest tool in createTools() with name, description, and input schema.
    {
      name: 'search_suggest',
      description: 'Search across accounts and items using full-text search. Returns matching entities with their full details.',
      inputSchema: {
        type: 'object',
        properties: {
          query: { type: 'string', description: 'Search query (searches titles, descriptions, names, emails, SKUs, etc.)' },
          types: {
            type: 'array',
            items: { type: 'string', enum: ['items', 'accounts'] },
            description: 'Entity types to search. Options: "items", "accounts". Leave empty to search both.'
          },
        },
        required: ['query'],
      },
    },
  • Helper method in ConsignCloudClient that performs the actual search by calling the API /search endpoint with query and optional types (mapped to entities).
    async search(query: string, entities?: string[]): Promise<any> {
      const params: any = { query };
      if (entities && entities.length > 0) {
        // ConsignCloud expects entities[] as array parameter
        params.entities = entities;
      }
      const response = await this.client.get('/search', { params });
      return response.data;
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it 'returns matching entities with their full details', which hints at output behavior, but lacks critical details like pagination, rate limits, authentication needs, error conditions, or whether it's a read-only operation. For a search tool with zero annotation coverage, this is insufficient for safe and effective use.

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 and front-loaded, consisting of just two sentences that efficiently convey the core functionality. Every word earns its place, with no redundancy or fluff, making it easy for an agent to parse quickly.

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 search tool with no annotations and no output schema, the description is incomplete. It doesn't explain return values, error handling, performance implications, or how results are structured. While the purpose is clear, the lack of behavioral and output details makes it inadequate for confident tool invocation in varied contexts.

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 documents both parameters ('query' and 'types') thoroughly. The description adds minimal value beyond the schema by implying the search scope ('accounts and items'), but doesn't provide additional syntax, format details, or examples. This meets the baseline of 3 when 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 tool's purpose: 'Search across accounts and items using full-text search. Returns matching entities with their full details.' It specifies the verb (search), resources (accounts and items), and scope (full-text search). However, it doesn't explicitly differentiate from sibling tools like 'suggest_field_values' or 'list_accounts/list_items', which is why it doesn't reach a 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. It doesn't mention when to prefer this over 'list_accounts' or 'list_items' for filtered results, or how it differs from 'suggest_field_values'. There's no context about prerequisites, exclusions, or specific use cases, leaving the agent to infer usage from the purpose alone.

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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