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hiveflowai

HiveFlow MCP Server

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by hiveflowai

get_flow_executions

Retrieve execution history for a specific automation flow to monitor performance and track past runs.

Instructions

Obtiene el historial de ejecuciones de un flujo

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flowIdYesID del flujo
limitNoLímite de resultados

Implementation Reference

  • The handler function that retrieves the execution history (processes) for a given flowId from the HiveFlow API, formats it as a formatted text list, and returns it in the MCP response format. Handles errors gracefully.
    async getFlowExecutions(args) {
      try {
        const response = await this.hiveflowClient.get(`/api/flows/${args.flowId}/processes`, {
          params: { limit: args.limit || 10 }
        });
        
        if (response.data && response.data.success) {
          const processes = response.data.processes || [];
          
          const executionsList = processes.map(process => 
            `• ${process.processId || process._id} - Estado: ${process.status} - ${process.startTime} ${process.endTime ? `(${process.duration}ms)` : '(en progreso)'}`
          ).join('\n');
          
          return {
            content: [
              {
                type: 'text',
                text: `📈 Ejecuciones del flujo (${processes.length}):\n\n${executionsList || 'No hay ejecuciones'}`
              }
            ]
          };
        } else {
          return {
            content: [
              {
                type: 'text',
                text: `❌ Error: ${response.data?.message || 'No se pudieron obtener las ejecuciones'}`
              }
            ]
          };
        }
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `❌ Error de conexión: ${error.message}`
            }
          ]
        };
      }
    }
  • src/index.js:185-203 (registration)
    The tool registration entry in the ListToolsRequestSchema handler, defining the name, description, and input schema (with flowId required and limit optional).
    {
      name: 'get_flow_executions',
      description: 'Obtiene el historial de ejecuciones de un flujo',
      inputSchema: {
        type: 'object',
        properties: {
          flowId: {
            type: 'string',
            description: 'ID del flujo'
          },
          limit: {
            type: 'number',
            description: 'Límite de resultados',
            default: 10
          }
        },
        required: ['flowId']
      }
    }
  • The input schema definition for the get_flow_executions tool, specifying parameters and validation.
    inputSchema: {
      type: 'object',
      properties: {
        flowId: {
          type: 'string',
          description: 'ID del flujo'
        },
        limit: {
          type: 'number',
          description: 'Límite de resultados',
          default: 10
        }
      },
      required: ['flowId']
    }
  • The switch case in the CallToolRequestSchema handler that routes calls to the getFlowExecutions method.
    case 'get_flow_executions':
      return await this.getFlowExecutions(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. It states the tool retrieves history, implying it's a read-only operation, but doesn't confirm this or describe other traits like rate limits, authentication needs, error conditions, or what the output looks like (e.g., list format, pagination). For a tool with zero annotation coverage, this is insufficient.

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

Conciseness4/5

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's appropriately sized for a simple tool, though it could be slightly more informative without losing conciseness. No structural issues are present.

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 moderate complexity (retrieving execution history with parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or output details, leaving significant gaps for an AI agent to understand how to invoke and interpret results effectively.

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?

The input schema has 100% description coverage, with clear documentation for both parameters ('flowId' and 'limit' with a default). The description doesn't add any meaning beyond the schema—it doesn't explain parameter interactions, valid formats for 'flowId', or how 'limit' affects results. Given the high schema coverage, a baseline score of 3 is appropriate as 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 action ('Obtiene el historial de ejecuciones') and resource ('de un flujo'), which translates to 'Gets the execution history of a flow'. It specifies what the tool does without being tautological. However, it doesn't explicitly differentiate from sibling tools like 'get_flow' or 'execute_flow', which prevents a perfect score.

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 choose this over 'get_flow' (which might retrieve flow metadata) or 'execute_flow' (which might trigger a new execution), nor does it specify prerequisites like needing an existing flow ID. This lack of contextual guidance limits its utility for an AI agent.

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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