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mcp-steampipe

by b0ttle-neck

スチームパイプMCP

これはシンプルなSteampipe MCPサーバーです。AIモデルとSteampipeツール間の橋渡しとして機能します。

前提条件

  • Python 3.10+ がインストールされています。

  • uv をインストールしました(私のお気に入り)そして mcp[cli]

  • Steampipe がインストールされ、動作しています。

  • 必要な資格情報 (例: ~/.steampipe/config/github.spc 内のトークン) を使用して構成された Steampipe プラグイン (例: github)。

  • MCPをサポートするLLMであればどれでも構いません。私はClaude Hereを使用しています。

  • Node.js と npx がインストールされています (MCP Inspector に必要であり、一部の MCP サーバーの実行にも必要になる可能性があります)。

Related MCP server: steam-mcp

MCPインターセプターの実行

これは、MCPサーバーが期待通りに動作しているかどうかをテストするための素晴らしいツールです。

  • インターセプターを実行するnpx -y @modelcontextprotocol/inspector uv --directory . run steampipe_mcp_server.py

  • ブラウザ ウィンドウが開き、MCP Inspector UI (通常はhttp://localhost:XXXX ) が表示されます。

  • 左側のパネルに「接続済み」ステータスが表示されるまで待ちます。

  • [ツール]タブに移動します。

  • run_steampipe_query ツールとその説明がリストされているはずです。

  • ツール名をクリックします。

  • 「引数」JSON 入力フィールドに、有効な Steampipe クエリを入力します。

{
  "query": "select name, fork_count from github_my_repository "
}
  • 実行してJSONの結果を表示する

ツールの実行

非常に簡単です。インターセプターを実行し、ディレクトリからツールが動作することを確認するだけです。その後、サーバー設定をそれぞれのLLMに追加し、LLMからツールを選択します。 スクリーンショット 2025-04-06 11:53 23PMスクリーンショット 2025-04-06 11:55 21PM

トラブルシューティング

  • インターセプター内にツールが見つからない場合は、@mcp.tool() デコレータに何らかの問題があることを意味します。

  • 実行エラー - インスペクターの「結果」とターミナルのサーバーログ(stderr)を確認してください。Steampipeは実行されましたか?SQLエラーは発生しましたか?タイムアウトは発生しましたか?JSON解析エラーは発生しましたか?状況に応じてPythonスクリプトを調整してください。

tail -f ~/Library/Logs/Claude/mcp.log
tail -f ~/Library/Logs/Claude/mcp-server-steampipe.log

セキュリティ リスクClaude はこの POC で SQL クエリを盲目的に実行するため、構成された資格情報を使用して Steampipe 経由で任意の SQL クエリを生成および実行する可能性があります。

Available Tools

1 tool
run_steampipe_queryB

Executes a SQL query using the Steampipe CLI and returns the results as a JSON string.

Args: query: The SQL query to execute via Steampipe (e.g., "select login from github_user limit 1"). Ensure the query is valid Steampipe SQL.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool executes a query and returns JSON results, but lacks critical details such as execution timeouts, error handling, authentication requirements, or rate limits. This leaves significant gaps in understanding how the tool behaves in practice.

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

Conciseness5/5

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

The description is well-structured and concise, with no wasted words. It starts with a clear purpose statement, followed by a labeled 'Args' section with a bullet point for the single parameter. Each sentence adds value, making it easy to scan and understand quickly.

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

Completeness3/5

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

Given the tool's complexity (executing SQL queries with potential side effects) and the lack of annotations and output schema, the description is moderately complete. It covers the basic purpose and parameter semantics but misses behavioral details like error responses, performance considerations, or output structure, which are important for a query execution tool.

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

Parameters4/5

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

The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that the 'query' parameter is 'The SQL query to execute via Steampipe' and provides an example, clarifying that it must be 'valid Steampipe SQL.' This compensates well for the schema's lack of detail, though it doesn't cover all potential edge cases.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Executes a SQL query using the Steampipe CLI and returns the results as a JSON string.' It specifies the verb ('executes'), resource ('SQL query'), and output format ('JSON string'). However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.

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?

The description provides minimal usage guidance. It includes an example query but does not specify when to use this tool versus other methods (e.g., direct database access or other query tools). There is no mention of prerequisites, error conditions, or typical use cases beyond the basic example.

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 updatev1.0.0
    • First observedrun_steampipe_query

TDQS

B3.3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The naming follows a clear verb_noun pattern (run_steampipe_query).

Tool Count2/5

A single tool is too few for most practical purposes, as it severely limits the server's functionality and flexibility. While it might cover the basic query execution, it lacks any supporting operations like listing available tables, checking query status, or managing connections.

Completeness2/5

The server is severely incomplete for interacting with Steampipe. It only provides query execution, missing essential operations such as listing available plugins/tables, describing table schemas, managing connections, or handling query errors and metadata. This will cause significant agent failures in complex workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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