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Python での Unichat MCP サーバー

TypeScriptでも利用可能

ツールまたは事前定義されたプロンプトを介して、MCPプロトコルを使用してOpenAI、MistralAI、Anthropic、xAI、Google AI、DeepSeek、Alibaba、Inceptionにリクエストを送信します。ベンダーAPIキーが必要です。

ツール

サーバーは 1 つのツールを実装します。

  • unichat : unichatにリクエストを送信する

    • 必須の文字列引数として「messages」を受け取ります

    • 応答を返す

プロンプト

  • code_review

    • ベストプラクティス、潜在的な問題、改善点についてコードをレビューする

    • 引数:

      • code (文字列、必須): レビューするコード

  • document_code

    • docstring やコメントを含むコードのドキュメントを生成する

    • 引数:

      • code (文字列、必須): コメントするコード

  • explain_code

    • コードがどのように動作するかを詳しく説明する

    • 引数:

      • code (文字列、必須): 説明するコード

  • code_rework

    • 提供されたコードに要求された変更を適用する

    • 引数:

      • changes (文字列、オプション): 適用する変更

      • code (文字列、必須): 再作業するコード

Related MCP server: MCP AI Gateway

クイックスタート

インストール

クロードデスクトップ

MacOS の場合: ~/Library/Application\ Support/Claude/claude_desktop_config.json Windows の場合: %APPDATA%/Claude/claude_desktop_config.json

対応モデル:

現在サポートされているモデルのリストは、 "SELECTED_UNICHAT_MODEL"としてこちらでご確認いただけます。関連するベンダーAPIキーを"YOUR_UNICHAT_API_KEY"として追加してください。

例:

"env": {
  "UNICHAT_MODEL": "gpt-4o-mini",
  "UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}

開発/非公開サーバーの構成

"mcpServers": {
  "unichat-mcp-server": {
    "command": "uv",
    "args": [
      "--directory",
      "{{your source code local directory}}/unichat-mcp-server",
      "run",
      "unichat-mcp-server"
    ],
    "env": {
      "UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
      "UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
    }
  }
}

公開サーバーの構成

"mcpServers": {
  "unichat-mcp-server": {
    "command": "uvx",
    "args": [
      "unichat-mcp-server"
    ],
    "env": {
      "UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
      "UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
    }
  }
}

Smithery経由でインストール

Smithery経由で Claude Desktop 用の Unichat を自動的にインストールするには:

npx -y @smithery/cli install unichat-mcp-server --client claude

発達

建築と出版

配布用のパッケージを準備するには:

  1. 古いビルドを削除します。

rm -rf dist
  1. 依存関係を同期し、ロックファイルを更新します。

uv sync
  1. パッケージディストリビューションをビルドします。

uv build

これにより、 dist/ディレクトリにソースとホイールのディストリビューションが作成されます。

  1. PyPI に公開:

uv publish --token {{YOUR_PYPI_API_TOKEN}}

デバッグ

MCPサーバーはstdio経由で実行されるため、デバッグが困難になる場合があります。最適なデバッグ環境を実現するには、 MCP Inspectorの使用を強くお勧めします。

次のコマンドを使用して、 npm経由で MCP Inspector を起動できます。

npx @modelcontextprotocol/inspector uv --directory {{your source code local directory}}/unichat-mcp-server run unichat-mcp-server

起動すると、ブラウザでアクセスしてデバッグを開始できる URL がインスペクタに表示されます。

Available Tools

1 tool
unichatC

Chat with an assistant. Example tool use message: Ask the unichat to review and evaluate your proposal.

ParametersJSON Schema
NameRequiredDescriptionDefault
messagesYesArray of exactly two messages: first a system message defining the task, then a user message with the specific query

TDQS

C2.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions nothing about behavioral traits like whether this is a read-only operation, if it requires authentication, rate limits, or what kind of responses to expect. The example hints at evaluation tasks but doesn't disclose operational characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief but includes an example that adds some value. However, the formatting with extra whitespace is awkward, and the example could be integrated more cleanly. It's not excessively verbose, but the structure could be improved for better front-loading of information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a chat tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the assistant does, what domains it covers, what format responses take, or any limitations. The example provides minimal context but doesn't compensate for the lack of structured information about this interactive tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents the single parameter (messages array with exactly two messages). The description adds no parameter information beyond what's in the schema, not even mentioning the two-message requirement. Baseline 3 is appropriate when schema does all the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Chat with an assistant' which indicates the basic function, but it's vague about what this assistant does or what domain it operates in. The example tool use message adds some context about reviewing proposals, but doesn't make the purpose specific or distinguish it from other chat tools. It's not tautological but lacks clear differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives is provided. The example suggests it can be used for reviewing proposals, but there's no mention of prerequisites, limitations, or when not to use it. With no sibling tools, the bar is lower, but still lacks basic usage context.

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.

  1. 1 tool update
    • First observedunichat

TDQS

C2.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'unichat' has a clear and distinct purpose of chatting with an assistant.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'unichat' follows a simple, readable pattern without any conflicting conventions.

Tool Count2/5

A single tool is too few for most server purposes, as it severely limits functionality and scope. While it might be appropriate for a minimal chat interface, it feels thin and lacks the depth expected for a typical MCP server, which usually requires multiple tools to handle different operations or resources.

Completeness3/5

For a chat assistant domain, the single tool 'unichat' covers the core action of chatting, but there are notable gaps. It lacks operations for managing chat history, configuring settings, or handling multiple sessions, which are common in chat systems. However, the basic functionality is present, allowing agents to perform the primary task.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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