Arkiv MCP Server
Arkiv MCP 서버
AI 에이전트와 애플리케이션에 Arkiv 데이터베이스 체인 쿼리 기능을 제공하는 Model Context Protocol (MCP) 서버입니다.
빠른 시작
1. 빌드
cd arkiv-mcp
npm install
npm run build2. Claude Code에 추가
arkiv-mcp 디렉토리에서 다음을 실행하세요:
claude mcp add arkiv -- node $(pwd)/dist/index.js또는 ~/.claude/settings.json에 수동으로 추가하세요:
{
"mcpServers": {
"arkiv": {
"command": "node",
"args": ["/absolute/path/to/arkiv-mcp/dist/index.js"]
}
}
}Claude Desktop의 경우, 동일한 블록을 ~/Library/Application Support/Claude/claude_desktop_config.json(macOS) 또는 %APPDATA%\Claude\claude_desktop_config.json(Windows)에 추가하세요.
3. Kaolin 테스트넷 쿼리
연결되면 query_entities 도구를 사용할 수 있습니다. 예시 프롬프트:
"Arkiv의 모든 엔티티 쿼리"
"
type = "post"이고score > 10인 모든 Arkiv 엔티티 찾기""Arkiv 테스트넷에서
0x1234...가 소유한 엔티티 보여줘""
status = "active"와 일치하는 첫 5개 엔티티를 가져온 후 페이지네이션"
Related MCP server: TextQL MCP Server
기능
SQL과 유사한 필터 표현식을 사용하여 Arkiv 데이터베이스 체인에서 엔티티 쿼리
전체
arkiv_query구문 지원: 비교, 논리 연산자, 글로브(glob) 매칭, 합성 속성커서를 사용한 페이지네이션 지원
구성 가능한 반환 필드 (속성, 메타데이터, 페이로드)
기본값으로 Kaolin 테스트넷 사용
설치
cd arkiv-mcp
npm install
npm run build
# Or use tsx for development
npm run dev사용법
서버 시작
# Using default Kaolin testnet
npm start
# With custom node URL
npm start -- --node-url https://your-arkiv-node.rpc
# Or with tsx for development
npm run dev -- --node-url https://your-arkiv-node.rpc환경 변수
변수 | 설명 | 필수 여부 |
| Arkiv 노드 RPC URL | 아니요 (기본값: Kaolin 테스트넷) |
명령줄 옵션
옵션 | 설명 | 기본값 |
| Arkiv 노드 RPC URL | Kaolin 테스트넷 |
| 도움말 표시 | - |
MCP 도구
query_entities
Arkiv 데이터베이스 체인에서 엔티티를 쿼리합니다.
매개변수
매개변수 | 타입 | 설명 | 기본값 |
| string | 필터 표현식 (아래 구문 참조) |
|
| number | 반환할 최대 엔티티 수 (최대 200) | - |
| string | 이전 응답에서 받은 페이지네이션 커서 | - |
| boolean | 결과에 속성 포함 여부 | true |
| boolean | 결과에 메타데이터(소유자, 생성자, 만료) 포함 여부 | true |
| boolean | 결과에 페이로드(base64 인코딩) 포함 여부 | true |
| number | 특정 블록 번호에서의 상태 쿼리 | - |
필터 구문
filter 매개변수는 arkiv_query 표현식 언어를 사용합니다:
연산자 | 설명 | 예시 |
| 같음 |
|
| 같지 않음 |
|
| 숫자 범위 |
|
| 논리 AND |
|
| 논리 OR |
|
| 부정 |
|
| 글로브 매칭 |
|
| 부정 글로브 매칭 |
|
합성 속성 ($ 접두사 사용):
속성 | 설명 |
| 모든 엔티티 매칭 |
| 현재 소유자 주소 |
| 원본 생성자 주소 (변경 불가) |
| 엔티티 키 |
필터 예시
# 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")응답 형식
{
"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
}다음 호출 시 반환된 cursor를 cursor 매개변수로 전달하여 페이지네이션을 수행합니다. cursor가 없으면 더 이상 결과가 없는 것입니다.
개발
이 서버는 다음을 사용합니다:
@arkiv-network/sdk — Arkiv TypeScript SDK
@modelcontextprotocol/sdk — MCP 서버 SDK
프로젝트 구조
arkiv-mcp/
├── src/
│ └── index.ts # Main server implementation
├── package.json
├── tsconfig.json
└── README.md라이선스
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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