Skip to main content
Glama
hiveflowai

HiveFlow MCP Server

Official
by hiveflowai

create_mcp_server

Register a new MCP server in HiveFlow to connect AI assistants to the automation platform for creating and managing workflows through natural language commands.

Instructions

Registra un nuevo servidor MCP en HiveFlow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesNombre único del servidor MCP
commandYesComando para ejecutar el servidor
argsNoArgumentos del comando
descriptionNoDescripción del servidor

Implementation Reference

  • The main handler function that implements the create_mcp_server tool. It sends a POST request to the HiveFlow API endpoint '/api/mcp/servers' with the provided arguments to register a new MCP server and returns a success message.
    async createMCPServer(args) {
      const response = await this.hiveflowClient.post('/api/mcp/servers', {
        name: args.name,
        command: args.command,
        args: args.args || [],
        description: args.description || ''
      });
      
      return {
        content: [
          {
            type: 'text',
            text: `✅ Servidor MCP "${args.name}" registrado exitosamente.\nComando: ${args.command}\nEstado: registrado`
          }
        ]
      };
    }
  • The tool specification in the ListTools response, including name, description, and inputSchema defining the required 'name' and 'command' parameters along with optional 'args' and 'description'.
    {
      name: 'create_mcp_server',
      description: 'Registra un nuevo servidor MCP en HiveFlow',
      inputSchema: {
        type: 'object',
        properties: {
          name: {
            type: 'string',
            description: 'Nombre único del servidor MCP'
          },
          command: {
            type: 'string',
            description: 'Comando para ejecutar el servidor'
          },
          args: {
            type: 'array',
            items: { type: 'string' },
            description: 'Argumentos del comando'
          },
          description: {
            type: 'string',
            description: 'Descripción del servidor'
          }
        },
        required: ['name', 'command']
      }
    },
  • src/index.js:228-229 (registration)
    The switch case in the CallToolRequestSchema handler that routes calls to the 'create_mcp_server' tool to its handler function.
    case 'create_mcp_server':
      return await this.createMCPServer(args);
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. While 'registra' implies a write/mutation operation, the description doesn't disclose what permissions are needed, whether this operation is idempotent, what happens if a server with the same name exists, or what the expected response format is. For a mutation tool with zero annotation coverage, this represents significant gaps in behavioral 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 gets straight to the point with zero wasted words. It's appropriately sized for the tool's function and front-loads the essential information.

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 mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after registration, what gets returned, error conditions, or how this operation fits into the broader MCP server lifecycle. Given the complexity of registering a new server and the lack of structured output information, the description should provide more context about the operation's consequences and results.

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?

With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('Registra' - registers) and the resource ('un nuevo servidor MCP en HiveFlow'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'create_flow' or 'list_mcp_servers' in terms of what makes this registration operation unique.

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 like 'list_mcp_servers' or other creation tools. There's no mention of prerequisites, appropriate contexts, or exclusions for this registration operation.

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/hiveflowai/hiveflow-mcp-server'

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