coderocket-mcp

deploy_repo

Analyze a repository and generate a CI/CD workflow, returning complete YAML and explanation. Handles the full async process automatically.

Instructions

Analyze a repository and generate a CI/CD workflow. Handles the full async flow internally (analyze → poll → generate → poll) and returns the complete YAML + explanation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "repo_id": "<repo_id>"
    },
    "name": "deploy_repo"
  }
}

Input Schema

Name	Required	Description	Default
`repo_id`	Yes	Repository ID from list_repos
`deploy_target`	No	Optional deploy target (e.g., 'aws-ecs', 'vercel', 'fly-io')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2Aug 7, 2026

TDQS

A4.2/5.0

Behavior4/5

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 the internal async flow ('analyze → poll → generate → poll') and the return format ('complete YAML + explanation'). This adds meaningful context about expected behavior and output.

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 two sentences with no filler. The first sentence states the core purpose, and the second clarifies the internal flow and return value. Every word earns its place.

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

Completeness4/5

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

For a tool with only 2 parameters, no annotations, and no output schema, the description covers the purpose, the async flow, and the return value. It could mention potential errors or prerequisites, but the given information is sufficient for basic understanding and usage.

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 schema provides 100% description coverage for both parameters (repo_id and deploy_target). The description does not add any additional parameter-level meaning, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Analyze a repository and generate a CI/CD workflow', which is a specific verb+resource combination. It distinguishes from siblings like list_repos, create_pr, and repo_details by focusing on CI/CD workflow generation rather than listing, PR creation, or repository details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context that this tool is used for generating CI/CD workflows and handles the async flow internally. While it doesn't explicitly exclude alternatives or name sibling tools, the use case is evident from the stated purpose and the sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server