# Vertex AI Agent Platform

> Skill: Vertex AI Model Context Protocol (MCP)

- Skill: `izzyfresh/vertex-ai-agent-platform` (Agent Skill)
- Install (CLI): `npx skillmds@latest add izzyfresh/vertex-ai-agent-platform`
- Raw SKILL.md: https://api.skillmd.com/api/skills/izzyfresh/vertex-ai-agent-platform/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: IzzyFresh (https://skillmd.com/u/izzyfresh)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/izzyfresh/vertex-ai-agent-platform

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# Skill: Vertex AI Model Context Protocol (MCP)

This skill outlines the rules for integrating, configuring, and registering Model Context Protocol (MCP) Servers within the Google Cloud Vertex Agent Platform.

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## 1. Structuring `toolspec.json`
*   The platform requires a strict JSON specification defining the tools exposed by your MCP server.
*   **Payload Format:** 
    ```json
    {
      "tools": [
        {
          "name": "example_tool_name",
          "description": "A highly detailed and unambiguous description of what the tool accomplishes.",
          "inputSchema": {
            "type": "object",
            "properties": {
              "param_1": {
                "type": "string",
                "description": "Clear definition of the input parameter."
              }
            },
            "required": ["param_1"]
          }
        }
      ]
    }
    ```
*   **Strictness:** All parameters in `inputSchema` must be strongly typed. Ambiguous types (like empty schema references) will cause the tool registry to fail.
# Skill: Vertex AI Agent Platform

This skill covers deployment parameters, packaging structures, and runtime configuration for hosting AI Agents on Google Cloud's Vertex platform.

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## 1. Packaging Standards
*   **Directory Structure:** Keep all Dialogflow CX lifecycle callbacks, JSON specs, and OpenAPI toolset configurations in their designated subdirectories.
*   **OpenAPI Toolsets:** OpenAPI schemas must be packaged into a ZIP bundle alongside the agent definitions when uploading to the Agent Studio.

## 2. Configuration
*   Ensure the `.agent_engine_config.json` file specifies the correct compute resource scaling parameters.
*   Always supply the explicit `--region` (or `--location`) parameter when invoking deployment scripts, as defaulting to regional configurations causes Cloud Build failures.