Masheev mcp

Official Agent Skills for integrating Masheev into your applications

Install

npx -y skills add masheev/skills --skill masheev-mcp

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Use when connecting Claude Code, Cursor, Copilot, or other AI coding tools to the Masheev API via MCP (Model Context Protocol). Covers installing the @masheev/mcp server, configuring authentication, and using the 4 available tools: list_api_endpoints, get_api_endpoint_schema, execute_api_endpoint, and get_api_categories. Use this skill when someone asks to "connect Masheev to Claude", "set up MCP for Masheev", or wants to manage Masheev from their AI coding environment.

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SKILL.md

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Masheev MCP Server

Connect AI coding tools to Masheev via the Model Context Protocol. This lets Claude Code, Cursor, Copilot, and other MCP-compatible tools discover and call Masheev API endpoints.

Installation

npm install -g @masheev/mcp

Configuration

Claude Code / Claude Desktop

Add to your MCP config (.claude/mcp.json or Claude Desktop settings):

{
  "mcpServers": {
    "masheev": {
      "command": "masheev-mcp",
      "env": {
        "MASHEEV_API_BASE_URL": "https://api.masheev.com",
        "MASHEEV_API_TOKEN": "your_api_key_here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "masheev": {
      "command": "npx",
      "args": ["-y", "@masheev/mcp"],
      "env": {
        "MASHEEV_API_BASE_URL": "https://api.masheev.com",
        "MASHEEV_API_TOKEN": "your_api_key_here"
      }
    }
  }
}

Available Tools

Tool	Description
`list_api_endpoints`	Search and browse all Masheev API endpoints. Accepts optional `query`, `category`, `tag`, `requiresAuth` filters.
`get_api_endpoint_schema`	Get the full OpenAPI schema for a specific endpoint (parameters, request/response types).
`execute_api_endpoint`	Execute an API endpoint with parameters. Handles routing (GET/DELETE -> query params, POST/PUT/PATCH -> body).
`get_api_categories`	List all API endpoint categories and their descriptions.

Environment Variables

Variable	Required	Default	Description
`MASHEEV_API_BASE_URL`	No	`http://localhost:3015`	Masheev API URL
`MASHEEV_API_TOKEN`	No	-	API key for authenticated endpoints
`API_PORT`	No	`3015`	API port (alternative to full URL)

Example Usage

Once configured, ask your AI coding tool:

"List all Masheev API endpoints related to contacts"
"Show me the schema for creating a conversation"
"Create a new webhook subscription for message events"
"Get the billing balance for my organization"

The AI tool will use the MCP server to discover endpoints, understand their schemas, and execute them on your behalf.

Gives 0 of the 12 instructions most mcp tooling skills give

Counted across 638 of the 750 authors here whose files we hold, read 2026-08-06

create ten complex read-only evaluation questionsin 71 of 638, across 17 files
test servers using MCP Inspectorin 60 of 638, across 18 files
provide actionable error messagesin 56 of 638, across 14 files
prioritize comprehensive API coverage over specific workflowsin 54 of 638, across 12 files
use TypeScript and Streamable HTTP for remote serversin 53 of 638, across 7 files
define structured output schemas where possiblein 51 of 638, across 9 files
use Zod or Pydantic for input schemasin 48 of 638, across 6 files
fetch MCP specification pages with markdown suffixin 46 of 638, across 4 files
load framework documentation using WebFetchin 45 of 638, across 3 files
verify each evaluation answer independentlyin 45 of 638, across 3 files
implement API client with authentication and paginationin 45 of 638, across 3 files
Define input schemas with validationin 28 of 638, across 10 files

Said here and by no other author read

use npx for cursor configuration

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.