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memgraph

Memgraph MCP Server

Official
by memgraph
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Python
Hybrid

[！重要]
このリポジトリは、ツールの重複を避けるためにMemgraph AI Toolkitモノレポに統合されました。
1 か月後に削除されます。今後の開発では、ここでのMCP 統合に従ってください。また、そのリポジトリで問題や PR を自由に開いてください。

🚀 Memgraph MCP サーバー

Memgraph MCP サーバーは、Memgraph を LLM に接続するために設計されたモデル コンテキスト プロトコル (MCP) の軽量サーバー実装です。

mcpサーバー

⚡ クイックスタート

📹 Memgraph MCP サーバー クイックスタート ビデオ

1. Memgraph MCPサーバーを実行する

  1. uvをインストールし、 uv venvでvenvを作成します。.venv .venv\Scripts\activateで仮想環境をアクティブ化します。

  2. 依存関係をインストール: uv add "mcp[cli]" httpx

  3. Memgraph MCP サーバーを実行します: uv run server.py 。

2. MCPクライアントを実行する

  1. Claude for Desktopをインストールします。

  2. Claude config に Memgraph サーバーを追加します。

macOS/Linux

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

ウィンドウズ

code $env:AppData\Claude\claude_desktop_config.json

設定例:

{
    "mcpServers": {
      "mpc-memgraph": {
        "command": "/Users/katelatte/.local/bin/uv",
        "args": [
            "--directory",
            "/Users/katelatte/projects/mcp-memgraph",
            "run",
            "server.py"
        ]
     }
   }
}

[！注記]
コマンドフィールドにuv実行ファイルへのフルパスを入力する必要がある場合があります。macOS/Linuxの場合はwhich uv 、Windowsの場合はwhere uv実行することで取得できます。サーバーへの絶対パスを必ず入力してください。

3. データベースとチャットする

  1. Memgraph MAGE を実行します。

    docker run -p 7687:7687 memgraph/memgraph-mage --schema-info-enabled=True

    LLM がSHOW SCHEMA INFOクエリを実行できるように、 --schema-info-enabled構成設定がTrueに設定されています。

  2. Claude Desktop を開いて、Memgraph のツールとリソースの一覧を確認してください。ぜひお試しください！（ Memgraph Labデータセットからダミーデータを読み込むことができます）

Related MCP server: mcp-graphql

🔧ツール

実行クエリ()

Memgraph に対して Cypher クエリを実行します。

🗃️ リソース

get_schema()

Memgraph スキーマ情報を取得します (前提条件: --schema-info-enabled=True )。

🗺️ ロードマップ

Memgraph MCPサーバーはまだ始まったばかりです。私たちは、その機能拡張と、Memgraphを最新のAIワークフローにさらに容易に統合するための開発に積極的に取り組んでいます。近い将来、JavaScriptベースの環境をより適切にサポートするために、TypeScript版のサーバーをリリースする予定です。さらに、このプロジェクトをAIツールキットの中央リポジトリに移行し、LangChain、LlamaIndex、MCP向けの他のツールや統合機能と連携させる予定です。私たちの目標は、Memgraphをコアとしたグラフベースのアプリケーションやインテリジェントエージェントをシームレスに構築できる、統合されたオープンソースツールキットを提供することです。

Available Tools

1 tool
run_queryC

Run a query against Memgraph

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is read-only or mutating, what permissions are needed, error handling, or performance implications (e.g., timeouts, rate limits). This leaves significant gaps for safe invocation.

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 a single, direct sentence with no wasted words—it's front-loaded and appropriately sized for a simple tool. Every word earns its place by stating the core action.

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?

Given no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral traits, parameter details, or return values, making it inadequate for a tool that likely executes database operations with potential side effects.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no parameter semantics beyond the schema's 'query' field. It doesn't explain what the query should contain (e.g., syntax, format), expected inputs, or constraints, failing to compensate for the low coverage.

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 'Run a query against Memgraph' clearly states the action (run) and target (Memgraph), but it's vague about what type of query (Cypher? SQL?) and what resources are affected. Without sibling tools, differentiation isn't needed, but the purpose remains somewhat generic.

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 guidance is provided on when to use this tool—there are no alternatives mentioned, no context for usage, and no prerequisites or exclusions. The description assumes the agent knows when to run queries without any framing.

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_query
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.8/5.0

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 name 'run_query' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a database server's apparent scope, as it severely limits functionality (e.g., no schema management, data manipulation beyond queries, or connection handling). This is a significant mismatch for the domain.

Completeness1/5

The tool surface is severely incomplete for a database server. It only supports running queries, lacking essential operations like creating/dropping databases, managing schemas, listing tables, or handling transactions, which will cause frequent agent failures.

Resources

Related MCP Connectors

Related MCP Servers

  • mcp-graphql

    launchthatbrand
    A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that enables LLMs to interact with GraphQL APIs by providing schema introspection and query execution capabilities.
    913 npm
    3
    MIT

  • MCP Database Server

    manpreet2000
    A
    license
    D
    quality
    D
    maintenance
    A Model Context Protocol server that enables LLMs to interact with databases (currently MongoDB) through natural language, supporting operations like querying, inserting, deleting documents, and running aggregation pipelines.
    5
    6 npm
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