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clarenous
by clarenous

get_tools

Retrieve available tools and workflows from the VeyraX platform to access their methods, parameters, and capabilities for integration.

Instructions

"Use this tool to retrieve a list of available tools from the Veyrax API. This will return dynamic tools that user has access to. You can use this tool to get the list of tools, method names and parameters, and then use tool_call tool to call the tool with the provided parameters. This method also returns all flows with name and id that user has access to (if any). "

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesQuery question that you want find answer for. Try to ALWAYS provide this field based on conversation with user. Could be your reasoning for calling tool.
toolYesGuess the tool name. Use explicit information based on the user's request or make an educated guess. It will be used for vector search for identifying the most relevant tools.

Implementation Reference

  • The execute method of GetToolsTool that handles the tool logic: constructs URL with optional 'question' and 'tool' query params, fetches from Veyrax API '/get-tools', formats response as MCP content block.
    async execute({ question, tool }: z.infer<typeof this.schema>) {
      try {
        let url = '/get-tools';
        const params = new URLSearchParams();
        
        if (question) params.append('question', question);
        if (tool) params.append('tool', tool);
        
        if (params.toString()) {
          url += `?${params.toString()}`;
        }
        
        const { data } = await veyraxClient.get(url);
    
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify(data, null, 2),
            },
          ],
        };
      } catch (error) {
        throw error;
      }
    }
  • Input schema using Zod: 'question' (string, conversation context/reasoning) and 'tool' (string, for filtering tools). Defines validation for tool parameters.
    schema = z.object({
      question: z.string()
        .describe("Query question that you want find answer for. Try to ALWAYS provide this field based on conversation with user. Could be your reasoning for calling tool."),
      tool: z.string()
        .describe("Guess the tool name. Use explicit information based on the user's request or make an educated guess. It will be used for vector search for identifying the most relevant tools.")
    });
  • src/index.ts:13-13 (registration)
    Registers the GetToolsTool with the MCP server in the main entry point.
    new GetToolsTool().register(server);
  • TypeScript interface for the get_tools response: object mapping tool names to their methods and parameters.
    export interface GetToolsResponse {
      tools: {
        [toolName: string]: Tool;
      };
    }
  • src/index.ts:4-4 (registration)
    Import statement for GetToolsTool used in registration.
    import { GetToolsTool } from "./tools/get-tools";

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.0
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

B3/5.0
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 the tool returns dynamic tools and flows based on user access, which adds some context about permissions and scope. However, it doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, error conditions, or response format details, leaving significant gaps for a tool that fetches system metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is reasonably concise at four sentences, but it could be more front-loaded. The first sentence states the core purpose, but subsequent sentences mix usage guidance and additional return details without a clear hierarchical structure. Some redundancy exists (e.g., mentioning tool list retrieval multiple times).

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 (fetching dynamic system metadata with access control), no annotations, and no output schema, the description is incomplete. It lacks details on return format (e.g., structure of tool/flow lists), error handling, authentication needs, or how the parameters influence results, making it inadequate for reliable agent 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?

Schema description coverage is 100%, so the schema fully documents the two required parameters (question and tool). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how these parameters affect the search or results. This meets the baseline for high schema coverage.

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: 'retrieve a list of available tools from the Veyrax API' and mentions it also returns flows. It specifies the verb ('retrieve') and resource ('list of available tools'), but doesn't explicitly differentiate from sibling tools like get_flow or tool_call, which would require 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides some implied usage guidance: it suggests using this tool to get tool information before calling tool_call, and mentions it returns dynamic tools and flows. However, it lacks explicit when-to-use rules, alternatives, or exclusions compared to siblings like get_flow, leaving room for ambiguity.

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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