Arkiv MCP Server
Arkiv MCPサーバー
Model Context Protocol (MCP)サーバーであり、AIエージェントやアプリケーションに対してArkivデータベースチェーンのクエリ機能を提供します。
クイックスタート
1. ビルド
cd arkiv-mcp
npm install
npm run build2. Claude Codeへの追加
arkiv-mcpディレクトリから以下を実行します:
claude mcp add arkiv -- node $(pwd)/dist/index.jsまたは、~/.claude/settings.jsonに手動で追加します:
{
"mcpServers": {
"arkiv": {
"command": "node",
"args": ["/absolute/path/to/arkiv-mcp/dist/index.js"]
}
}
}Claude Desktopの場合は、同じブロックを~/Library/Application Support/Claude/claude_desktop_config.json(macOS)または%APPDATA%\Claude\claude_desktop_config.json(Windows)に追加してください。
3. Kaolinテストネットへのクエリ
接続が完了すると、query_entitiesツールが利用可能になります。プロンプトの例:
"Query all entities on Arkiv"
"Find all Arkiv entities where
type = "post"andscore > 10""Show me entities owned by
0x1234...on the Arkiv testnet""Get the first 5 entities matching
status = "active", then paginate"
Related MCP server: TextQL MCP Server
機能
SQLライクなフィルタ式を使用したArkivデータベースチェーンからのエンティティクエリ
完全な
arkiv_query構文:比較、論理演算子、グロブマッチング、合成属性カーソルによるページネーションサポート
設定可能な戻り値フィールド(属性、メタデータ、ペイロード)
デフォルトでKaolinテストネットを使用
インストール
cd arkiv-mcp
npm install
npm run build
# Or use tsx for development
npm run dev使用方法
サーバーの起動
# Using default Kaolin testnet
npm start
# With custom node URL
npm start -- --node-url https://your-arkiv-node.rpc
# Or with tsx for development
npm run dev -- --node-url https://your-arkiv-node.rpc環境変数
変数 | 説明 | 必須 |
| ArkivノードのRPC URL | いいえ(デフォルトはKaolinテストネット) |
コマンドラインオプション
オプション | 説明 | デフォルト |
| ArkivノードのRPC URL | Kaolinテストネット |
| ヘルプを表示 | - |
MCPツール
query_entities
Arkivデータベースチェーンからエンティティをクエリします。
パラメータ
パラメータ | 型 | 説明 | デフォルト |
| string | フィルタ式(以下の構文を参照) |
|
| number | 返されるエンティティの最大数(最大200) | - |
| string | 前回のレスポンスからのページネーションカーソル | - |
| boolean | 結果に属性を含める | true |
| boolean | 結果にメタデータ(所有者、作成者、有効期限)を含める | true |
| boolean | 結果にペイロード(base64エンコード)を含める | true |
| number | 特定のブロック番号時点の状態をクエリ | - |
フィルタ構文
filterパラメータはarkiv_query式言語を使用します:
演算子 | 説明 | 例 |
| 等価 |
|
| 非等価 |
|
| 数値範囲 |
|
| 論理AND |
|
| 論理OR |
|
| 否定 |
|
| グロブマッチ |
|
| 否定グロブ |
|
合成属性($で始まるもの):
属性 | 説明 |
| すべてのエンティティに一致 |
| 現在の所有者アドレス |
| 元の作成者アドレス(不変) |
| エンティティキー |
フィルタの例
# All entities
$all
# By entity key
$key = "0xabc123..."
# By owner or creator
$owner = "0x1234567890abcdef..."
$creator = "0x1234567890abcdef..."
# Attribute equality
status = "active"
type = "post"
# Numeric range
score > 100
price >= 50 && price <= 200
# Compound
project = "myapp" && type = "post" && score > 10
# Glob matching
name ~ "draft*"
!(status = "deleted")レスポンス形式
{
"entities": [
{
"key": "0x...",
"owner": "0x...",
"creator": "0x...",
"createdAtBlock": "12345",
"lastModifiedAtBlock": "12350",
"expiresAtBlock": "99999",
"contentType": "application/json",
"payload": "<base64-encoded bytes>",
"attributes": [
{ "key": "type", "value": "post" },
{ "key": "score", "value": 42 }
]
}
],
"cursor": "0x2a",
"blockNumber": "12350",
"count": 1
}ページネーションを行うには、返されたcursorを次の呼び出しのcursorパラメータとして渡します。cursorが存在しない場合、それ以上の結果はありません。
開発
このサーバーは以下を使用しています:
@arkiv-network/sdk — Arkiv TypeScript SDK
@modelcontextprotocol/sdk — MCPサーバーSDK
プロジェクト構造
arkiv-mcp/
├── src/
│ └── index.ts # Main server implementation
├── package.json
├── tsconfig.json
└── README.mdライセンス
MIT
Available Tools
1 toolquery_entitiesA
Query entities from an Arkiv database chain using a filter expression. The filter uses a SQL-like syntax: comparisons (=, !=, <, >, <=, >=), logical operators (&& and ||), negation (!), and glob matching (~). Special attributes: $all (match everything), $owner (current owner address), $creator (original creator address, immutable), $key (entity key). Examples: '$all', 'status = "active"', 'score > 100', 'project = "myapp" && status = "active"', '$owner = "0x1234..."', 'name ~ "test*"'
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No | Filter expression. Defaults to "$all" if omitted. Examples: 'status = "active"', 'score > 100 && type = "post"', '$owner = "0xAbc..."', '$creator = "0xDef..."', 'name ~ "prefix*"' | |
| limit | No | Maximum number of entities to return (max 200) | |
| cursor | No | Pagination cursor returned by a previous query | |
| withAttributes | No | Include attributes in results (default: true) | |
| withMetadata | No | Include metadata (owner, creator, expiry) in results (default: true) | |
| withPayload | No | Include payload in results as base64 (default: true) | |
| validAtBlock | No | Query state at a specific block number |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the filter syntax and special attributes but does not disclose performance implications, rate limits, or confirm that it is read-only. Schema covers some aspects (e.g., limit), but behavioral context is lacking.
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?
The description is a single, well-structured paragraph that front-loads the core purpose, then details the filter syntax, special attributes, and examples. Every sentence adds value without redundancy.
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?
Given no output schema, the description does not explain return values explicitly, but the tool name and parameters imply entities with requested fields. Pagination cursor is mentioned in schema but not explained in description. Overall, it is fairly complete for a query tool.
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?
Schema description coverage is 100%, so baseline is 3. The description adds meaningful context for the 'filter' parameter by detailing the syntax and special attributes ($all, $owner, etc.), which goes beyond the schema. Other parameters are not enhanced, but the main parameter benefits significantly.
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?
The description clearly states that the tool queries entities from an Arkiv database chain using a filter expression, with specific SQL-like syntax and special attributes. It is a specific verb-resource pair, and there are no sibling tools to distinguish against.
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?
The description provides examples and syntax details that imply when to use the tool, but does not explicitly state when not to use or mention alternatives. Since there are no sibling tools, the lack of exclusion is less critical.
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 tool update
v1.0.0- First observed
query_entities
TDQS
Scored across 1 tool
Only one tool exists, so there is no risk of confusion between tools. Perfect disambiguation.
With a single tool, there are no naming inconsistencies. The name 'query_entities' follows a clear verb_noun pattern.
A single tool is insufficient for a database server; even if it's query-only, missing CRUD operations severely limits functionality. Extreme mismatch.
The server only offers query functionality, omitting essential operations like create, update, or delete. Significant gaps for typical database interaction.
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