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cuongdev

AWS CodePipeline MCP Server

by cuongdev

list_pipeline_executions

Retrieve execution history for an AWS CodePipeline to monitor deployment status and track changes.

Instructions

List executions for a specific pipeline

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipelineNameYesName of the pipeline

Implementation Reference

  • The core handler function for the 'list_pipeline_executions' MCP tool. It takes a pipelineName, calls AWS CodePipeline SDK to list executions, formats the response, and returns it as MCP content.
    export async function listPipelineExecutions(codePipelineManager: CodePipelineManager, input: { pipelineName: string }) {
      const { pipelineName } = input;
      const codepipeline = codePipelineManager.getCodePipeline();
      
      const response = await codepipeline.listPipelineExecutions({ 
        pipelineName 
      }).promise();
      
      const executions = response.pipelineExecutionSummaries?.map((execution: AWS.CodePipeline.PipelineExecutionSummary) => ({
        pipelineExecutionId: execution.pipelineExecutionId || '',
        status: execution.status || '',
        startTime: execution.startTime?.toISOString() || '',
        lastUpdateTime: execution.lastUpdateTime?.toISOString() || '',
        sourceRevisions: execution.sourceRevisions?.map((revision: AWS.CodePipeline.SourceRevision) => ({
          name: revision.actionName || '',
          revisionId: revision.revisionId || '',
          revisionUrl: revision.revisionUrl || '',
          revisionSummary: revision.revisionSummary || ''
        })) || []
      })) || [];
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify({ executions }, null, 2),
          },
        ],
      };
    }
  • The input schema definition for the 'list_pipeline_executions' tool, specifying the required pipelineName parameter.
    export const listPipelineExecutionsSchema = {
      name: "list_pipeline_executions",
      description: "List executions for a specific pipeline",
      inputSchema: {
        type: "object",
        properties: {
          pipelineName: { 
            type: "string",
            description: "Name of the pipeline"
          }
        },
        required: ["pipelineName"],
      },
    } as const;
  • src/index.ts:144-146 (registration)
    Registration of the tool handler in the MCP CallToolRequestHandler switch statement. Dispatches calls to the listPipelineExecutions function.
    case "list_pipeline_executions": {
      return await listPipelineExecutions(codePipelineManager, input as { pipelineName: string });
    }
  • src/index.ts:115-115 (registration)
    The tool schema is registered in the ListToolsRequestHandler response, making it discoverable by MCP clients.
    listPipelineExecutionsSchema,
  • src/index.ts:20-22 (registration)
    Import statement that brings in the handler and schema from the tools directory.
      listPipelineExecutions, 
      listPipelineExecutionsSchema 
    } from "./tools/list_pipeline_executions.js";
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List executions') but does not describe traits like pagination, sorting, filtering options, rate limits, authentication needs, or what data is returned (e.g., list of execution objects). For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 directly states the tool's purpose without unnecessary words. It is front-loaded with the core action ('List executions') and specifies the scope ('for a specific pipeline'), making it easy to parse quickly. There is no wasted verbiage or redundancy.

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 listing executions (which may involve multiple attributes like status, timestamps, IDs) and the lack of annotations and output schema, the description is incomplete. It does not explain what information is returned, how results are structured, or any behavioral aspects like limits or ordering. For a tool with no structured output documentation, the description should provide more context to be fully helpful.

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%, with the parameter 'pipelineName' fully documented in the schema as 'Name of the pipeline'. The description adds no additional meaning beyond this, such as format examples (e.g., case sensitivity) or constraints (e.g., must be an existing pipeline). With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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 verb ('List') and resource ('executions for a specific pipeline'), making the purpose understandable. It distinguishes from siblings like 'list_pipelines' (which lists pipelines rather than executions) and 'get_pipeline_execution_logs' (which gets logs for a specific execution). However, it lacks specificity about what 'executions' entails (e.g., status, timestamps, IDs), keeping it from 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 does not mention prerequisites (e.g., needing a valid pipeline name), exclusions (e.g., not for real-time monitoring), or comparisons to siblings like 'get_pipeline_state' (which might show current state) or 'list_pipelines' (for broader listing). Usage is implied by the name but not explicitly stated.

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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