GMI Cloud Documentation
GMI Cloud documentation MCP server (Mintlify-hosted on docs.gmicloud.ai) exposing documentation search and retrieval; tools/list answered anonymously with HTTP 200 on 2026-10-13. It is a docs MCP, not an MCP over the platform API.
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Endpoint
Hosted endpoint · transport http
Connect
This is a remote MCP server — point an MCP client at the endpoint URL. Clients with native remote support (Claude, Cursor, VS Code, …):
For stdio-only clients (older Claude Desktop, etc.), bridge with mcp-remote:
If the server requires authentication, add the provider's token/header (e.g. an X-API-Key) per its docs. A quick reachability check:
Tool quality observed · not scored
tools with readOnly / destructive hints
parameters described (4 total)
state-changing tools without destructiveHint
tool-list tokens (3 tools)
tools over ~1,200 tokens
From an anonymous initialize + tools/list capture measured 2026-10-27; tokens are chars/3.6 of each tool definition. Recorded for the Kin Score's agent readiness as an observed signal — it contributes no points yet.
Tools
search_gmi_cloud_documentation— Search across the GMI Cloud Documentation knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about GMI Cloud Documentation, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages. Ifquery_docs_filesystem_gmi_cloud_documentation— Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at `/` that contains ONLY the GMI Cloud Documentation documentation pages and OpenAPI specs. This is NOT a shell on any real machine — nothing runs on the user's computer, the server host, or any network. The filesystem is a sandbox backed by documentation chunks. This is how you read documentation pages: there issubmit_feedback— Report a problem with this documentation site so the docs team can fix it. Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example. This is for feedback about the documentation content itself — not for product support requests or feedback about this tool or assistant.
About MCP
The Model Context Protocol (MCP) is an open protocol Anthropic introduced for connecting LLM-based agents to external tools and data sources. Providers publish MCP servers that expose their API surface as structured, discoverable tools — an MCP-compatible client (Claude Desktop, Cursor, Cline, Continue, etc.) can connect to the server and call its tools without any per-provider integration code.
Browse every MCP server on the APIs.io network or compare with the broader Agent Skill surfaces of the same providers.
Work with this as data
Every MCP server here is available over the APIs.io API and to AI agents over MCP.