mcp-google-agent-platform-docs
Provides search and retrieval of Google AI platform documentation, including Gemini Enterprise Agent Platform (GEAP) and legacy Vertex AI documentation.
mcp-google-agent-platform-docs
MCP server providing Google AI platform documentation to AI agents.
Part of OpenGerwin MCP Servers
What is this?
An MCP (Model Context Protocol) server that gives AI agents direct access to Google's AI platform documentation — both the current Gemini Enterprise Agent Platform (GEAP) and the legacy Vertex AI Generative AI docs.
Instead of hallucinating API details, your AI assistant can look up the actual documentation in real-time.
Related MCP server: RAG Docs MCP Server
Features
🔍 Full-text search across 3400+ documentation pages
📄 On-demand fetching — pages are downloaded and cached as you need them
🗂️ Dual source — current GEAP + legacy Vertex AI documentation
⚡ Smart caching — 72-hour TTL, stale fallback on network errors
🗺️ Auto-discovery — new pages found via sitemap scanning (weekly)
🧩 Plug & play — works with Claude Desktop, Cursor, VS Code, any MCP client
Quick Start
Install
# Using pip
pip install mcp-google-agent-platform-docs
# Using uv (recommended)
uv pip install mcp-google-agent-platform-docsConfigure Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"google-agent-platform-docs": {
"command": "mcp-google-agent-platform-docs"
}
}
}Configure Antigravity (Google)
Add to ~/.gemini/antigravity/mcp_config.json:
{
"mcpServers": {
"google-agent-platform-docs": {
"command": "uv",
"args": [
"--directory",
"/path/to/mcp-google-agent-platform-docs",
"run",
"mcp-google-agent-platform-docs"
]
}
}
}Configure Cursor / VS Code
Add to your MCP settings:
{
"mcpServers": {
"google-agent-platform-docs": {
"command": "mcp-google-agent-platform-docs",
"transport": "stdio"
}
}
}Tools
search_docs
Search documentation by keywords.
search_docs("Memory Bank setup", source="geap")
search_docs("function calling", source="vertex-ai")get_doc
Get full content of a specific page.
get_doc("scale/memory-bank/setup", source="geap")
get_doc("multimodal/function-calling", source="vertex-ai")list_sections
Browse documentation structure.
list_sections(source="geap")list_models
Quick reference for all available AI models (Gemini, Imagen, Veo, Claude, etc.).
list_models()Documentation Sources
Source ID | Platform | Pages | Status |
| Gemini Enterprise Agent Platform | 2300+ | Primary (current) |
| Vertex AI Generative AI | 1100+ | Legacy (archive) |
GEAP Sections
Agent Studio — Visual agent builder
Agents → Build — Runtime, ADK, Agent Garden, RAG Engine
Agents → Scale — Sessions, Memory Bank, Code Execution
Agents → Govern — Policies, Agent Gateway, Model Armor
Agents → Optimize — Observability, Evaluation, Quality Alerts
Models — Gemini, Imagen, Veo, Lyria, Partners, Open Models
Notebooks — Jupyter tutorials
Configuration
Environment variables for customization:
Variable | Default | Description |
|
| Cache directory |
|
| Page cache TTL (hours) |
|
| Structure cache TTL (days) |
|
| Default documentation source |
|
| HTTP timeout (seconds) |
Development
# Clone
git clone https://github.com/OpenGerwin/mcp-google-agent-platform-docs.git
cd mcp-google-agent-platform-docs
# Install dependencies
uv sync
# Run server locally
uv run mcp-google-agent-platform-docs
# Test with MCP Inspector
uv run mcp dev src/mcp_google_agent_platform_docs/server.pyArchitecture
mcp-google-agent-platform-docs/
├── sources/ # YAML source configurations
│ ├── geap.yaml # GEAP (primary)
│ └── vertex-ai.yaml # Vertex AI (legacy)
├── src/mcp_google_agent_platform_docs/
│ ├── server.py # FastMCP server + 4 tools
│ ├── source.py # Source model (YAML loader)
│ ├── fetcher.py # HTML → Markdown converter
│ ├── cache.py # TTL cache manager
│ ├── discovery.py # Sitemap-based page discovery
│ ├── search.py # TF-IDF search engine
│ └── config.py # Global configuration
└── tests/License
MIT — see LICENSE.
Part of OpenGerwin MCP Servers
Maintenance
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