pulsemcp Safe content atomic mcp-remote

Image Gen (Jimeng AI)

This MCP server, developed by an unknown author, provides a lightweight implementation for handling MCP requests. Built with Python and leveraging the aiohttp and aiofiles libraries, it offers asynchronous capabilities for efficient request processing. The server focuses on basic functionality, utilizing the fastmcp and mcp libraries for core MCP operations. It's designed for developers who need a simple, customizable MCP server solution, enabling use cases such as prototyping MCP-based applications, testing MCP integrations, or serving as a foundation for more complex MCP implementations.

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: media
Source: PulseMCP
Repository: github.com/fengin/image-gen-server
Author type: human
Updated: 2026-05-21

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MCP

Resolve Image Gen (Jimeng AI) 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"