mcp-google-agent-platform-docs
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MCP_DOCS_CACHE_DIR | No | Cache directory | ~/.cache/mcp-google-agent-platform-docs |
| MCP_DOCS_CONTENT_TTL | No | Page cache TTL (hours) | 72 |
| MCP_DOCS_HTTP_TIMEOUT | No | HTTP timeout (seconds) | 30 |
| MCP_DOCS_STRUCTURE_TTL | No | Structure cache TTL (days) | 7 |
| MCP_DOCS_DEFAULT_SOURCE | No | Default documentation source | geap |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_docsA | Search Google AI platform documentation. Args: query: Search terms (e.g. "function calling", "Memory Bank setup", "Agent Development Kit", "Gemini 3.1 Pro") max_results: Number of results to return (default: 5, max: 20) source: Documentation source: - "geap" (default) — Gemini Enterprise Agent Platform (current) - "vertex-ai" — Vertex AI Generative AI (legacy) Returns: Matching documentation pages with titles, paths, and excerpts. Use get_doc(path) to read the full content of any result. |
| get_docA | Get full content of a specific documentation page. Args: path: Documentation page path, e.g.: GEAP paths: - "models/gemini/3-1-pro" - "build/runtime/quickstart" - "scale/memory-bank/setup" - "govern/policies/overview" - "optimize/evaluation/agent-evaluation" - "agent-studio/overview" Vertex AI paths: - "multimodal/function-calling" - "rag-engine/rag-overview" - "models/gemini/2-5-flash" source: "geap" (default) or "vertex-ai" Returns: Complete page content in Markdown format. If not cached, fetches live from the documentation site. |
| list_sectionsB | List all documentation sections and their page counts. Args: source: "geap" (default) or "vertex-ai" Returns: Structured overview of all available documentation sections with descriptions and page counts. |
| list_modelsA | List all available AI models on Google's platform. Returns a quick reference of all models organized by family: Google (Gemini, Imagen, Veo, Lyria), Partners (Claude, Grok, Mistral, Llama), and Open Models (DeepSeek, Qwen, Kimi, etc.). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a distinct purpose: get_doc retrieves page content, list_models lists models, list_sections lists documentation sections, and search_docs searches across docs. No ambiguity.
All tool names follow a consistent verb_noun pattern (get_doc, list_models, list_sections, search_docs), making them predictable and easy to understand.
With 4 tools, the server is well-scoped for a documentation access interface, covering essential operations without bloat.
The tool set provides comprehensive coverage for documentation: listing models, browsing sections, searching, and retrieving full content. No obvious gaps.