Multi-Service Gateway
This modular MCP server implementation provides a standardized way for AI models to interact with external tools and services through a unified gateway. It includes five specialized tools: GitHub for repository management, GitLab for project interactions, Google Maps for location services, Memory for persistent data storage, and Puppeteer for web automation. Built with Flask and designed for deployment on Red Hat environments, it features containerized deployment options using Podman or Docker, comprehensive error handling, and seamless integration with OpenAI and Anthropic LLMs through standardized request/response formats.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- version-control
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Multi-Service Gateway 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 --scope user for --scope project to commit it to .mcp.json.