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mcp-메모리-libsql

libSQL 기반의 모델 컨텍스트 프로토콜(MCP)을 위한 고성능 영구 메모리 시스템입니다. 이 서버는 libSQL을 백업 저장소로 사용하여 벡터 검색 기능과 효율적인 지식 저장 기능을 제공합니다.

특징

  • 🚀 libSQL을 사용한 고성능 벡터 검색

  • 💾 엔티티 및 관계의 영구 저장

  • 🔍 의미 검색 기능

  • 🔄 지식 그래프 관리

  • 🌐 로컬 및 원격 libSQL 데이터베이스와 호환

  • 🔒 원격 데이터베이스를 위한 보안 토큰 기반 인증

Related MCP server: MCP Memory LibSQL Go

구성

이 서버는 MCP 구성의 일부로 사용하도록 설계되었습니다. 다음은 다양한 환경에 대한 예시입니다.

클라인 구성

Cline MCP 설정에 다음을 추가하세요.

지엑스피1

WSL 구성을 사용한 Claude Desktop

WSL에서 Claude Desktop을 사용하여 이 서버를 설정하는 방법에 대한 자세한 가이드는 WSL에서 Claude Desktop을 사용하여 MCP 서버 작동시키기를 참조하세요.

WSL 환경에 대한 Claude Desktop 구성에 다음을 추가하세요.

{
	"mcpServers": {
		"mcp-memory-libsql": {
			"command": "wsl.exe",
			"args": [
				"bash",
				"-c",
				"source ~/.nvm/nvm.sh && LIBSQL_URL=file:/path/to/database.db /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-memory-libsql"
			]
		}
	}
}

데이터베이스 구성

서버는 LIBSQL_URL 환경 변수를 통해 로컬 SQLite와 원격 libSQL 데이터베이스를 모두 지원합니다.

로컬 SQLite 데이터베이스의 경우:

{
	"env": {
		"LIBSQL_URL": "file:/path/to/database.db"
	}
}

원격 libSQL 데이터베이스(예: Turso)의 경우:

{
	"env": {
		"LIBSQL_URL": "libsql://your-database.turso.io",
		"LIBSQL_AUTH_TOKEN": "your-auth-token"
	}
}

참고: WSL을 사용할 때 데이터베이스 경로가 Windows 형식이 아닌 Linux 파일 시스템 형식(예: /home/username/... )을 사용하는지 확인하세요.

기본적으로 URL이 제공되지 않으면 현재 디렉토리의 file:/memory-tool.db 사용합니다.

API

서버는 추가적인 벡터 검색 기능을 갖춘 표준 MCP 메모리 인터페이스를 구현합니다.

  • 엔티티 관리

    • 임베딩을 사용하여 엔터티 생성/업데이트

    • 엔터티 삭제

    • 유사성으로 엔터티 검색

  • 관계 관리

    • 엔터티 간 관계 생성

    • 관계 삭제

    • 관련 엔터티 쿼리

건축학

서버는 다음 스키마를 가진 libSQL 데이터베이스를 사용합니다.

  • 엔터티 테이블: 엔터티 정보 및 임베딩을 저장합니다.

  • 관계 테이블: 엔터티 간의 관계를 저장합니다.

  • libSQL의 내장 벡터 연산을 사용하여 구현된 벡터 검색 기능

개발

출판

npm 2FA 요구 사항으로 인해 게시는 수동으로 수행해야 합니다.

  1. 변경 세트를 만듭니다(변경 사항을 문서화합니다):

pnpm changeset
  1. 패키지 버전(버전 및 CHANGELOG 업데이트):

pnpm changeset version
  1. npm에 게시합니다(2FA 코드를 입력하라는 메시지가 표시됨):

pnpm release

기여하다

기여를 환영합니다! 풀 리퀘스트를 제출하기 전에 기여 지침을 꼭 읽어주세요.

특허

MIT 라이센스 - 자세한 내용은 LICENSE 파일을 참조하세요.

감사의 말

Available Tools

6 tools
create_entitiesC

Create new entities with observations and optional embeddings

ParametersJSON Schema
NameRequiredDescriptionDefault
entitiesYes

TDQS

C2.9/5.0
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 this is a creation operation, implying mutation, but doesn't cover critical aspects like permissions needed, whether it's idempotent, error handling, or rate limits. The mention of 'optional embeddings' hints at functionality but lacks depth on behavioral traits.

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, efficient sentence that front-loads the core action ('Create new entities') and adds key details ('with observations and optional embeddings'). There is no wasted wording, making it easy to parse quickly while conveying essential 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?

Given the tool's complexity (1 parameter with nested objects, no annotations, no output schema), the description is insufficient. It doesn't explain the return values, error conditions, or the full scope of parameters (e.g., 'relations'). For a creation tool with rich input structure, more context is needed to guide effective use.

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 0%, so the description must compensate. It mentions 'observations and optional embeddings', which partially maps to the schema's 'observations' and 'embedding' fields, but omits 'relations' and details on 'entityType' or 'name'. This adds some meaning but doesn't fully explain the single parameter's structure or all nested fields, leaving gaps.

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 action ('Create') and resource ('new entities'), specifying they include 'observations and optional embeddings'. This distinguishes it from siblings like 'create_relations' (which creates relationships) and 'delete_entity' (which removes entities). However, it doesn't explicitly mention the 'relations' parameter shown in the schema, leaving the purpose slightly incomplete.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., when entities should be created vs. updated), contrast with siblings like 'read_graph' or 'search_nodes', or specify scenarios where embeddings or relations are appropriate. This leaves the agent without contextual usage cues.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

create_relationsC

Create relations between entities

ParametersJSON Schema
NameRequiredDescriptionDefault
relationsYes

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Create relations' which implies a write/mutation operation, but doesn't specify permissions needed, whether it's idempotent, error handling, or what happens on success/failure. It lacks details on rate limits, side effects, or response format, leaving significant gaps for a mutation tool.

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 extremely concise with a single sentence 'Create relations between entities'. It's front-loaded and wastes no words, though this brevity contributes to underspecification in other dimensions. Every word serves a purpose, making it efficient in structure.

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 the tool's complexity (mutation operation with 1 parameter involving nested objects), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, parameter meanings, or expected outcomes, making it inadequate for safe and effective use by an AI agent.

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?

The description adds no parameter semantics beyond the input schema. With 0% schema description coverage and 1 parameter ('relations' array of objects with source, target, type), the description doesn't explain what these fields mean, valid values for 'type', or examples. It fails to compensate for the schema's lack of descriptions, leaving parameters poorly documented.

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 'Create relations between entities' clearly states the action (create) and resource (relations between entities), but it's vague about what 'entities' refers to and doesn't distinguish from sibling tools like 'create_entities' or 'delete_relation'. It provides basic purpose but lacks specificity about the domain or system context.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., entities must exist first), exclusions, or comparisons to siblings like 'create_entities' (for creating entities) or 'delete_relation' (for removing relations). Usage context is implied but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

delete_entityA

Delete an entity and all its associated data (observations and relations)

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesName of the entity to delete

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses the destructive nature ('Delete... and all its associated data'), which is crucial behavioral context. However, it lacks details on permissions needed, error conditions, or what happens if the entity doesn't exist.

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, efficient sentence that front-loads the core action and scope. Every word contributes meaning without redundancy, making it appropriately sized for a one-parameter tool.

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?

For a destructive mutation tool with no annotations and no output schema, the description adequately covers the basic action and scope. However, it lacks important context about permissions, confirmation requirements, or return values, leaving gaps for safe agent operation.

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%, providing a clear parameter description. The tool description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline for high schema coverage without compensating value.

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

Purpose5/5

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

The description clearly states the specific action ('Delete') and target resource ('an entity and all its associated data'), with explicit mention of what gets deleted ('observations and relations'). It distinguishes from sibling tools like 'delete_relation' by specifying broader scope.

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 on when to use this tool versus alternatives is provided. While the description implies destructive deletion, it doesn't specify prerequisites, warn about irreversible changes, or mention when to choose 'delete_entity' over 'delete_relation' or other siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

delete_relationC

Delete a specific relation between entities

ParametersJSON Schema
NameRequiredDescriptionDefault
sourceYesSource entity name
targetYesTarget entity name
typeYesType of relation

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states 'Delete', implying a destructive mutation, but doesn't disclose behavioral traits such as whether deletion is permanent, requires specific permissions, has side effects (e.g., cascading deletions), or what happens on success/failure. This is a significant gap for a mutation tool with zero annotation coverage.

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, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the core action without unnecessary elaboration, making it easy to parse quickly.

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 the complexity of a destructive operation with no annotations and no output schema, the description is incomplete. It lacks crucial context like what 'delete' entails (e.g., irreversible), expected outcomes, error handling, or how it differs from sibling tools. For a mutation tool, this minimal description is inadequate.

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 already documents all three parameters (source, target, type) with basic descriptions. The description adds no additional meaning beyond what the schema provides, such as examples of relation types or how entities are identified. Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Delete') and the resource ('a specific relation between entities'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'delete_entity' or 'create_relations', which would require specifying what makes this tool unique for relation deletion versus entity deletion or relation creation.

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 no guidance on when to use this tool versus alternatives. With siblings like 'delete_entity' and 'create_relations', it's unclear if this is for removing existing relations only, or if there are prerequisites (e.g., the relation must exist). No explicit when/when-not or alternative tools are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

read_graphC

Get recent entities and their relations

ParametersJSON Schema
NameRequiredDescriptionDefault
includeEmbeddingsNoWhether to include embeddings in the returned entities (default: false)

TDQS

C2.6/5.0
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 for behavioral disclosure. It mentions 'recent' but doesn't clarify how recency is determined (e.g., time-based, count-based). It also doesn't describe what 'entities and their relations' includes (e.g., format, structure, pagination) or any limitations (e.g., rate limits, authentication needs). The description is too minimal for a tool with potential complexity.

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

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action ('Get recent entities and their relations'). However, it could be more structured by explicitly separating purpose from constraints, but given its brevity, it's appropriately concise.

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 the lack of annotations and output schema, the description is incomplete for a tool that reads graph data. It doesn't explain what 'recent' entails, the format of returned entities/relations, or any behavioral aspects like error handling. For a tool with potential complexity in graph operations, this minimal description leaves significant gaps.

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?

The input schema has 1 parameter with 100% description coverage, so the schema fully documents 'includeEmbeddings'. The description adds no parameter information beyond what the schema provides. Since schema coverage is high, the baseline score is 3, as the description doesn't need to compensate but also adds no extra value.

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 the tool 'Get recent entities and their relations', which provides a basic verb+resource combination. However, it's vague about what 'recent' means (timeframe, recency criteria) and doesn't distinguish this tool from sibling tools like 'search_nodes' or 'create_entities' that also involve entities. The purpose is understandable but lacks specificity.

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 no guidance on when to use this tool versus alternatives. With siblings like 'search_nodes' (which might filter entities) and 'create_entities' (which creates rather than reads), there's no indication of when 'read_graph' is appropriate versus these other tools. No exclusions, prerequisites, or alternative suggestions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_nodesC

Search for entities and their relations using text or vector similarity

ParametersJSON Schema
NameRequiredDescriptionDefault
includeEmbeddingsNoWhether to include embeddings in the returned entities (default: false)
queryYes

TDQS

C2.9/5.0
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 mentions the search functionality but lacks details on permissions, rate limits, response format, or potential side effects (e.g., whether it's read-only or has other impacts). This is inadequate for a search tool with no structured safety hints.

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, efficient sentence that front-loads the core purpose without unnecessary words. It directly communicates the tool's function and method, making it easy to parse and understand quickly.

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 the complexity of a search tool with no annotations, no output schema, and incomplete parameter coverage, the description is insufficient. It lacks details on return values, error handling, or behavioral traits, leaving significant gaps for an AI agent to operate effectively.

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 50% (one of two parameters has a description). The description adds value by explaining the query parameter supports 'text or vector similarity,' which clarifies the oneOf schema, but it doesn't address the includeEmbeddings parameter or provide additional semantic context beyond the schema's basic descriptions.

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 as 'Search for entities and their relations using text or vector similarity,' which specifies the verb (search), resource (entities and their relations), and method (text or vector similarity). However, it doesn't explicitly differentiate from sibling tools like 'read_graph,' which might also involve reading/searching operations, leaving room for ambiguity.

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 no guidance on when to use this tool versus alternatives. It mentions the search methods (text or vector similarity) but doesn't specify scenarios, prerequisites, or exclusions compared to siblings like 'read_graph,' leaving the agent without clear 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. 6 tool updatesv1.0.0
    • First observedcreate_entities
    • First observedcreate_relations
    • First observeddelete_entity
    • First observeddelete_relation
    • First observedread_graph
    • First observedsearch_nodes

TDQS

B3.3/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: create_entities and create_relations handle creation of different object types, delete_entity and delete_relation handle deletion of different object types, read_graph retrieves recent data, and search_nodes performs searches. No ambiguity exists between these operations.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case naming: create_entities, create_relations, delete_entity, delete_relation, read_graph, and search_nodes. The naming is perfectly predictable and uniform throughout the set.

Tool Count5/5

With 6 tools, this server is well-scoped for a memory/graph database system. Each tool earns its place by covering essential CRUD operations (create, delete, read/search) for both entities and relations, without being overly complex or insufficient.

Completeness4/5

The tool set provides strong coverage for core graph operations: creation and deletion of entities/relations, reading recent data, and searching. A minor gap exists in update operations (e.g., update_entity or update_relation), but agents can work around this by deleting and recreating as needed.

Maintenance

ActivityInactive
ResponsivenessNo issues

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