Remote MCP Server (Authless)
Cloudflare 上でリモート MCP サーバーを構築する (認証なし)
https://remote-mcp-server-authless.feraranas.workers.dev/
Cloudflare 上でリモート MCP サーバーを構築する (認証なし)
この例では、Cloudflare Workers で認証を必要としないリモート MCP サーバーをデプロイできます。
始めましょう:
これにより、MCP サーバーが次のような URL にデプロイされます: remote-mcp-server-authless.<your-account>.workers.dev/sse
あるいは、以下のコマンド ラインを使用して、ローカル マシンにリモート MCP サーバーを作成することもできます。
npm create cloudflare@latest -- my-mcp-server --template=cloudflare/ai/demos/remote-mcp-authlessRelated MCP server: Remote MCP Server Authless
MCPサーバーのカスタマイズ
独自のツールを MCP サーバーに追加するには、 this.server.tool(...)を使用してsrc/index.tsのinit()メソッド内で各ツールを定義します。
Cloudflare AI Playgroundに接続する
リモート MCP クライアントである Cloudflare AI Playground から MCP サーバーに接続できます。
https://playground.ai.cloudflare.com/にアクセスしてください
デプロイされた MCP サーバーの URL を入力します (
remote-mcp-server-authless.<your-account>.workers.dev/sse)MCP ツールをプレイグラウンドから直接使用できるようになりました。
Claude DesktopをMCPサーバーに接続する
mcp-remote プロキシを使用して、ローカル MCP クライアントからリモート MCP サーバーに接続することもできます。
Claude Desktop から MCP サーバーに接続するには、 Anthropic のクイックスタートに従い、Claude Desktop 内で [設定] > [開発] > [構成の編集] に移動します。
次の構成で更新します。
{
"mcpServers": {
"calculator": {
"command": "npx",
"args": [
"mcp-remote",
"http://localhost:8787/sse" // or remote-mcp-server-authless.your-account.workers.dev/sse
]
}
}
}Claude を再起動すると、ツールが利用可能になるはずです。
Available Tools
2 toolsaddD
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculateD
| Name | Required | Description | Default |
|---|---|---|---|
| operation | Yes | ||
| a | Yes | ||
| b | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
add - First observed
calculate
TDQS
Scored across 2 tools
The two tools 'add' and 'calculate' are highly ambiguous without descriptions, as 'add' could be a subset of 'calculate' or vice versa, making it impossible to distinguish their purposes. This overlap creates a high risk of misselection, as agents cannot determine when to use one over the other based on the limited information provided.
The tool names 'add' and 'calculate' are both simple verbs, which provides some readability, but they lack a consistent pattern such as verb_noun or clear domain-specific conventions. The naming is mixed in style, with 'add' being a basic operation and 'calculate' being more general, but without descriptions, it's unclear if this reflects intentional design or inconsistency.
With only 2 tools, the server feels thin and under-scoped for most practical purposes, suggesting it may not cover a meaningful domain adequately. This low count is borderline inappropriate unless the server's purpose is extremely narrow, but without descriptions, it's hard to justify such minimalism, leaning toward too few tools for effective agent use.
The server is severely incomplete, as the lack of descriptions makes it impossible to infer a domain or assess coverage. With only vague tool names like 'add' and 'calculate', there are obvious gaps in any potential workflow, and agents will likely fail due to missing operations or unclear scope, rendering the tool surface non-functional for typical tasks.
Maintenance
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