MCP_implementation

A set of implementation rules for building an MCP server, a service that gives AI applications structured access to data, actions, and reusable message templates.

In plain words
What is it for?
It guides the implementation of resources for supplying data, tools for running actions, prompts for reusable interactions, and the server transport.
Why use it?
It explains how to expose server features and connect the TypeScript server to an MCP client.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/chriscarrollsmith/taskqueue-mcp/mcp_implementation
Clone the repo
git clone --depth 1 https://github.com/chriscarrollsmith/taskqueue-mcp

Made for: Cursor.

Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 439 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00439
Opus 5 $0.00000 $0.00219
Sonnet 5 $0.00000 $0.00088
Haiku 4.5 $0.00000 $0.00044

Measured 2d ago against content hash b0d8d7228f0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

MCP_implementation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/MCP_implementation.mdc · 72 lines

What it actually says

MCP TypeScript SDK

What is MCP?

The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but specifically designed for LLM interactions. MCP servers can:

  • Expose data through Resources (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
  • Provide functionality through Tools (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)
  • Define interaction patterns through Prompts (reusable templates for LLM interactions)

Running Your Server

MCP servers in TypeScript need to be connected to a transport to communicate with clients.

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
  ListPromptsRequestSchema,
  GetPromptRequestSchema
} from "@modelcontextprotocol/sdk/types.js";

const server = new Server(
  {
    name: "example-server",
    version: "1.0.0"
  },
  {
    capabilities: {
      prompts: {}
    }
  }
);

server.setRequestHandler(ListPromptsRequestSchema, async () => {
  return {
    prompts: [{
      name: "example-prompt",
      description: "An example prompt template",
      arguments: [{
        name: "arg1",
        description: "Example argument",
        required: true
      }]
    }]
  };
});

server.setRequestHandler(GetPromptRequestSchema, async (request) => {
  if (request.params.name !== "example-prompt") {
    throw new Error("Unknown prompt");
  }
  return {
    description: "Example prompt",
    messages: [{
      role: "user",
      content: {
        type: "text",
        text: "Example prompt text"
      }
    }]
  };
});

const transport = new StdioServerTransport();
await server.connect(transport);
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 72 lines · 0 tokens per session scan A b0d8d7228f0c

Subscribe to this mod's changes

MCP_implementation is a cursor rule published in the GitHub repository chriscarrollsmith/taskqueue-mcp (70 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 439 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.