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HiveFlow MCP Server

list_mcp_servers

Lists configured MCP servers within the HiveFlow automation platform to help AI assistants manage and execute flows through natural language commands.

Instructions

Lista los servidores MCP configurados en HiveFlow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function that executes the 'list_mcp_servers' tool logic: fetches the list of MCP servers from the HiveFlow API endpoint '/api/mcp/servers', formats them into a bullet list with status and connection info, and returns a structured text response.
    async listMCPServers() {
      const response = await this.hiveflowClient.get('/api/mcp/servers');
      const servers = response.data.servers || [];
      
      const serversList = servers.map(server => 
        `• ${server.name} - Estado: ${server.status} (${server.isConnected ? 'Conectado' : 'Desconectado'})`
      ).join('\n');
      
      return {
        content: [
          {
            type: 'text',
            text: `🔌 Servidores MCP (${servers.length}):\n\n${serversList || 'No hay servidores MCP configurados'}`
          }
        ]
      };
    }
  • The tool schema definition in the listTools response, specifying the name, description, and empty inputSchema (no input parameters required).
    {
      name: 'list_mcp_servers',
      description: 'Lista los servidores MCP configurados en HiveFlow',
      inputSchema: {
        type: 'object',
        properties: {}
      }
    },
  • src/index.js:225-226 (registration)
    The dispatch registration in the CallToolRequestHandler switch statement that routes calls to the 'list_mcp_servers' tool to its handler function.
    case 'list_mcp_servers':
      return await this.listMCPServers();
  • Identical handler function implementation in the TypeScript version of the server.
    private async listMCPServers() {
      const response = await this.hiveflowClient.get('/api/mcp/servers');
      const servers = response.data.servers || [];
      
      const serversList = servers.map((server: any) => 
        `• ${server.name} - Estado: ${server.status} (${server.isConnected ? 'Conectado' : 'Desconectado'})`
      ).join('\n');
      
      return {
        content: [
          {
            type: 'text',
            text: `🔌 Servidores MCP (${servers.length}):\n\n${serversList || 'No hay servidores MCP configurados'}`
          }
        ]
      };
    }
  • The tool schema definition in the TypeScript version.
    {
      name: 'list_mcp_servers',
      description: 'Lista los servidores MCP configurados en HiveFlow',
      inputSchema: {
        type: 'object',
        properties: {}
      }
    },
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions listing configured MCP servers but doesn't describe what 'configured' entails, whether the list is filtered or complete, how results are returned (e.g., format, pagination), or any permissions required. For a tool with zero annotation coverage, this leaves significant behavioral 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 a single, efficient sentence in Spanish that directly states the tool's purpose without unnecessary words. It is appropriately sized for a simple listing tool and front-loaded with the core action. There is zero waste, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It states what the tool does but lacks details on behavior, output format, or usage context. For a listing tool with no structured metadata, the description should provide more completeness, such as explaining what 'configured' means or how results are presented.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics beyond what the schema provides. A baseline of 4 is appropriate for a parameterless tool where the schema fully covers the input structure.

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 ('Lista') and resource ('servidores MCP configurados en HiveFlow'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'list_flows', but the resource specificity (MCP servers vs flows) provides implicit distinction. The description is not tautological and communicates a specific function.

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. There are sibling tools like 'list_flows' and 'get_flow' that might be relevant for related queries, but no explicit comparison or context is given. The description only states what the tool does, not when it should be selected over other options.

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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