pulsemcp Safe content atomic mcp-remote

AI Expert Workflow

AI Expert Workflow MCP is a server implementation that facilitates structured collaboration with AI experts in product development. Developed by bacoco, it provides access to three specialized AI roles: Product Manager, UX Designer, and Software Architect, each generating comprehensive documentation based on user requirements. The server uses OpenRouter API for flexible model selection and includes Task Master integration for converting product requirements into actionable development tasks. This implementation is particularly valuable for teams seeking to streamline the planning-to-implementation pipeline through expert consultation and document generation.

Cognium trust score

50%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: devops-ci
Source: PulseMCP
Repository: github.com/bacoco/ai-expert-workflow-mcp
Author type: human
Updated: 2026-05-27

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MCP

Resolve AI Expert Workflow from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

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

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"