# Enterprise SDLC MCP

> Enterprise SDLC MCP — raghuram-chittibomma-enterprise-sdlc-mcp. Use this tool when you need to streamline software development lifecycle (SDLC) tasks, such as product analysis, solution architecture, and code review, in GitHub-first projects. It provides reusable SDLC agent roles and review checklists, enabling AI coding agents to execute structured tasks. Ideal for projects requiring standardized and efficient SDLC management, it takes in project requirements and outputs structured review reports and release management plans.

Canonical page: https://skillsregistry.net/skills/raghuram-chittibomma-enterprise-sdlc-mcp  
JSON: https://api.skillsregistry.net/v1/skills/raghuram-chittibomma-enterprise-sdlc-mcp

## Description

Serves reusable SDLC agent roles and review checklists over MCP, enabling AI coding agents to execute structured product analysis, solution architecture, code review, and release management tasks in GitHub-first projects.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/osjkln2v3p)
- **Repository:** <https://github.com/raghuram-chittibomma/enterprise-sdlc-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "raghuram-chittibomma-enterprise-sdlc-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/raghuram-chittibomma-enterprise-sdlc-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/raghuram-chittibomma-enterprise-sdlc-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt