Skip to main content
Glama
CircleCI-Public

mcp-server-circleci

Official

config_helper

Analyze and validate CircleCI configuration files to identify errors and ensure proper syntax for pipeline execution.

Instructions

This tool helps analyze and validate and fix CircleCI configuration files.

Parameters:

  • params: An object containing:

    • configFile: string - The full contents of the CircleCI config file as a string. This should be the raw YAML content, not a file path.

Example usage: { "params": { "configFile": "version: 2.1 orbs: node: circleci/node@7 ..." } }

Note: The configFile content should be provided as a properly escaped string with newlines represented as .

Tool output instructions: - If the config is invalid, the tool will return the errors and the original config. Use the errors to fix the config. - If the config is valid, do nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo

Implementation Reference

  • The main handler function for the 'config_helper' tool. It validates the provided CircleCI config file using the CircleCI client's configValidate method and returns a success or error message.
    export const configHelper: ToolCallback<{
      params: typeof configHelperInputSchema;
    }> = async (args) => {
      const { configFile } = args.params ?? {};
    
      const circleci = getCircleCIClient();
      const configValidate = await circleci.configValidate.validateConfig({
        config: configFile,
      });
    
      if (configValidate.valid) {
        return {
          content: [
            {
              type: 'text',
              text: 'Your config is valid!',
            },
          ],
        };
      }
    
      return {
        content: [
          {
            type: 'text',
            text: `There are some issues with your config: ${configValidate.errors?.map((error) => error.message).join('\n') ?? 'Unknown error'}`,
          },
        ],
      };
    };
  • Zod input schema defining the 'configFile' parameter for the config_helper tool.
    export const configHelperInputSchema = z.object({
      configFile: z
        .string()
        .describe(
          'The contents of the circleci config file. This should be the contents of the circleci config file, not the path to the file. Typically located at .circleci/config.yml',
        ),
    });
  • Defines the tool object for 'config_helper' including name, description, and input schema.
    export const configHelperTool = {
      name: 'config_helper' as const,
      description: `
      This tool helps analyze and validate and fix CircleCI configuration files.
    
      Parameters:
      - params: An object containing:
        - configFile: string - The full contents of the CircleCI config file as a string. This should be the raw YAML content, not a file path.
    
      Example usage:
      {
        "params": {
          "configFile": "version: 2.1\norbs:\n  node: circleci/node@7\n..."
        }
      }
    
      Note: The configFile content should be provided as a properly escaped string with newlines represented as \n.
    
      Tool output instructions:
        - If the config is invalid, the tool will return the errors and the original config. Use the errors to fix the config.
        - If the config is valid, do nothing.
      `,
      inputSchema: configHelperInputSchema,
    };
  • Registers the configHelperTool in the main CCI_TOOLS array.
    export const CCI_TOOLS = [
      getBuildFailureLogsTool,
      getFlakyTestLogsTool,
      getLatestPipelineStatusTool,
      getJobTestResultsTool,
      configHelperTool,
      createPromptTemplateTool,
      recommendPromptTemplateTestsTool,
      runPipelineTool,
      listFollowedProjectsTool,
      runEvaluationTestsTool,
      rerunWorkflowTool,
      downloadUsageApiDataTool,
      findUnderusedResourceClassesTool,
      analyzeDiffTool,
      runRollbackPipelineTool,
      listComponentVersionsTool,
    ];
  • Maps the 'config_helper' name to its handler function in CCI_HANDLERS.
    export const CCI_HANDLERS = {
      get_build_failure_logs: getBuildFailureLogs,
      find_flaky_tests: getFlakyTestLogs,
      get_latest_pipeline_status: getLatestPipelineStatus,
      get_job_test_results: getJobTestResults,
      config_helper: configHelper,
      create_prompt_template: createPromptTemplate,
      recommend_prompt_template_tests: recommendPromptTemplateTests,
      run_pipeline: runPipeline,
      list_followed_projects: listFollowedProjects,
      run_evaluation_tests: runEvaluationTests,
      rerun_workflow: rerunWorkflow,
      download_usage_api_data: downloadUsageApiData,
      find_underused_resource_classes: findUnderusedResourceClasses,
      analyze_diff: analyzeDiff,
      run_rollback_pipeline: runRollbackPipeline,
      list_component_versions: listComponentVersions,
    } satisfies ToolHandlers;
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool analyzes, validates, and fixes configs; it returns errors and original config if invalid, and does nothing if valid. However, it misses details like rate limits, authentication needs, or whether 'fix' is automated or suggested, which are important for a mutation tool.

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 front-loaded with the purpose but includes redundant sections like 'Parameters:' that repeat schema info. The example and notes are helpful but could be more streamlined. Overall, it's adequately sized but has some inefficiencies in structure.

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 no annotations, no output schema, and 1 parameter with 0% schema coverage, the description provides basic completeness: purpose, param details, and output behavior. However, for a tool that 'fixes' configs (implying mutation), it lacks critical context like side effects, error handling specifics, or return format details, making it minimally adequate.

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 schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the schema: it explains that 'configFile' is the raw YAML content as a string, not a file path, and provides an example with formatting notes. This clarifies usage effectively, though it could detail YAML structure or constraints more.

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: 'analyze and validate and fix CircleCI configuration files.' It specifies the verb ('analyze, validate, fix') and resource ('CircleCI configuration files'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'run_pipeline' or 'rerun_workflow', which might involve config validation indirectly.

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 implies usage context through the example and output instructions, suggesting this tool is for validating configs before execution. However, it lacks explicit guidance on when to use this versus alternatives (e.g., 'run_pipeline' might handle validation internally) or any prerequisites, leaving some ambiguity for the agent.

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/CircleCI-Public/mcp-server-circleci'

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