pulsemcp Safe content atomic mcp-remote

Build MCP

This MCP server provides integration with build and deployment systems through HTTP-based APIs, built using Python with async support and YAML configuration management. The implementation includes a GD SDK service for interacting with external build platforms, structured logging capabilities, and comprehensive test coverage for both common utilities and service integrations. Designed for development teams and DevOps workflows that need programmatic access to build systems, deployment pipelines, and CI/CD operations through a standardized MCP interface with configurable endpoints and robust error handling.

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/869413421/build_mcp
Author type: human
Updated: 2026-05-24

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MCP

Resolve Build MCP 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"