이 프로젝트는 Omi API와 상호 작용하기 위한 모델 컨텍스트 프로토콜(MCP) 서버를 제공합니다. 이 서버는 대화와 기억을 읽고 새로운 대화와 기억을 생성하는 도구를 제공합니다.
저장소를 복제합니다
npm install 로 종속성 설치
다음 변수를 사용하여 .env 파일을 만듭니다.
지엑스피1
Related MCP server: Omi Memories MCP Server
Smithery를 통해 Claude Desktop에 Omi MCP 서버를 자동으로 설치하려면:
npx -y @smithery/cli install @fourcolors/omi-mcp --client claudenpm run buildnpm run start핫 리로딩을 사용한 개발의 경우:
npm run devMCP 서버와 상호 작용하기 위한 간단한 테스트 클라이언트가 포함되어 있습니다. 프로젝트를 빌드한 후 다음을 실행하세요.
npm run test또는 직접:
./test-mcp-client.js이렇게 하면 MCP 서버가 시작되고 사용 가능한 도구를 테스트할 수 있는 대화형 메뉴가 제공됩니다. 테스트 클라이언트는 모든 작업에 기본 테스트 사용자 ID( test-user-123 )를 사용합니다.
빌드 디렉토리를 정리하고 처음부터 다시 빌드하려면:
npm run rebuildAnthropic Console이나 API를 통해 Claude와 함께 이 MCP 서버를 사용하려면:
MCP 서버를 로컬로 시작합니다.
npm run startClaude 대화를 설정할 때 MCP 연결을 구성하세요.
{
"mcp_config": {
"transports": [
{
"type": "stdio",
"executable": {
"path": "/path/to/your/omi-mcp-local/dist/index.js",
"args": []
}
}
]
}
}클로드에게 보내는 예시 프롬프트:
Please fetch the latest 5 conversations for user "user123" using the Omi API.Claude는 MCP를 사용하여 read_omi_conversations 도구를 실행합니다.
{
"id": "req-1",
"type": "request",
"method": "tools.read_omi_conversations",
"params": {
"user_id": "user123",
"limit": 5
}
}커서와 함께 이 MCP 서버를 사용하려면:
터미널에서 MCP 서버를 시작합니다.
npm run start커서에서 설정 > 확장 프로그램 > MCP 서버로 이동합니다.
다음 설정으로 새로운 MCP 서버를 추가합니다.
이름: Omi API
URL: stdio:/path/to/your/omi-mcp-local/dist/index.js
서버를 활성화하세요
이제 커서 내에서 Omi 도구를 직접 사용할 수 있습니다. 예:
@Omi API Please fetch memories for user "user123" and summarize them.커서는 MCP 서버와 통신하여 필요한 API 호출을 실행합니다.
MCP 서버는 다음과 같은 도구를 제공합니다.
선택적 필터를 사용하여 특정 사용자의 Omi 대화를 검색합니다.
매개변수:
user_id (문자열): 대화를 가져올 사용자 ID
limit (숫자, 선택 사항): 반환할 대화의 최대 수
offset (숫자, 선택 사항): 페이지 매김을 위해 건너뛸 대화 수
include_discarded (부울, 선택 사항): 삭제된 대화를 포함할지 여부
statuses (문자열, 선택 사항): 대화를 필터링할 상태의 쉼표로 구분된 목록
특정 사용자의 오미로부터 기억을 검색합니다.
매개변수:
user_id (문자열): 메모리를 가져올 사용자 ID
limit (숫자, 선택 사항): 반환할 최대 메모리 수
offset (숫자, 선택 사항): 페이지 매김을 위해 건너뛸 메모리 수
특정 사용자에 대한 Omi에서 새로운 대화를 만듭니다.
매개변수:
text (문자열): 대화의 전체 텍스트 내용
user_id (문자열): 대화를 생성할 사용자 ID
text_source (문자열): 텍스트 콘텐츠의 소스(옵션: "audio_transcript", "message", "other_text")
started_at (문자열, 선택 사항): 대화/이벤트가 시작된 시간(ISO 8601 형식)
finished_at (문자열, 선택 사항): 대화/이벤트가 종료된 시점(ISO 8601 형식)
language (문자열, 선택 사항): 언어 코드(기본값: "en")
geolocation (객체, 선택 사항): 대화에 대한 위치 데이터
latitude (숫자): 위도 좌표
longitude (숫자): 경도 좌표
text_source_spec (문자열, 선택 사항): 소스에 대한 추가 사양
특정 사용자를 위해 오미에서 새로운 추억을 만듭니다.
매개변수:
user_id (문자열): 메모리를 생성할 사용자 ID
text (문자열, 선택 사항): 메모리를 추출할 텍스트 콘텐츠
memories (배열, 선택 사항): 직접 생성할 명시적 메모리 객체의 배열
content (문자열): 메모리의 내용
tags (문자열 배열, 선택 사항): 메모리에 대한 태그
text_source (문자열, 선택 사항): 텍스트 콘텐츠의 소스
text_source_spec (문자열, 선택 사항): 소스에 대한 추가 사양
MCP 서버를 테스트하려면 제공된 테스트 클라이언트를 사용할 수 있습니다.
node test-mcp-client.js이렇게 하면 다음 작업을 수행할 수 있는 대화형 테스트 클라이언트가 시작됩니다.
대화를 시작하세요
추억을 얻으세요
대화를 만들어 보세요
그만두다
테스트 클라이언트는 모든 작업에 기본 테스트 사용자 ID( test-user-123 )를 사용합니다.
MCP 서버에는 콘솔과 로그 파일 모두에 기록하는 로깅 기능이 내장되어 있습니다. 이 기능은 서버 활동 디버깅 및 모니터링에 유용합니다.
로그는 프로젝트 디렉터리의 logs/mcp-server.log 에 기록됩니다. 로그 파일에는 타임스탬프와 다음 항목에 대한 자세한 정보가 포함되어 있습니다.
서버 시작 및 종료
모든 API 요청 및 응답
오류 메시지 및 스택 추적
Omi에 대한 API 호출
요청 매개변수 및 응답 데이터
tail 명령을 사용하면 실시간으로 로그를 볼 수 있습니다.
tail -f logs/mcp-server.log이를 통해 서버가 요청을 처리하고 Omi API와 상호 작용할 때 실시간 업데이트가 표시됩니다.
각 로그 항목은 다음 형식을 따릅니다.
[2024-03-21T12:34:56.789Z] Log message here타임스탬프는 ISO 8601 형식이므로 이벤트를 쉽게 연관시키고 문제를 디버깅할 수 있습니다.
Creates a new Omi conversation with text content and metadata
| Name | Required | Description | Default |
|---|---|---|---|
| finished_at | No | When the conversation/event ended in ISO 8601 format. Optional. | |
| geolocation | No | Location data for the conversation. Optional object containing latitude and longitude. | |
| language | No | Language code (e.g., "en" for English). Optional, defaults to "en". | en |
| started_at | No | When the conversation/event started in ISO 8601 format. Optional. | |
| text | Yes | The full text content of the conversation | |
| text_source | Yes | Source of the text content. Required. Options: "audio_transcript", "message", "other_text". | |
| text_source_spec | No | Additional specification about the source. Optional. | |
| user_id | Yes | The user ID to create the conversation for |
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 it's a write/mutation tool, but doesn't disclose any behavioral traits like permission requirements, rate limits, side effects, or what happens on success/failure. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a creation tool, though it could potentially benefit from slightly more context given the lack of annotations and usage guidelines.
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 the complexity (8 parameters, nested objects, no output schema, and no annotations), the description is insufficient. It doesn't explain what a successful creation returns, error conditions, or behavioral constraints. For a creation tool with multiple parameters and no structured safety hints, more descriptive context is needed to be complete.
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?
The schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'text content and metadata', which loosely maps to the 'text' and other fields. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
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 the verb 'creates' and the resource 'new Omi conversation', specifying it includes 'text content and metadata'. This distinguishes it from sibling tools like 'read_omi_conversations' (read vs. create) and 'create_omi_memories' (conversation vs. memories). However, it doesn't explicitly differentiate from 'create_omi_memories' beyond the resource name.
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 no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'create_omi_memories' or whether it's for initial conversation creation versus updates. There's no context about prerequisites, dependencies, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Creates Omi memories by extracting from text or using explicit memory objects
| Name | Required | Description | Default |
|---|---|---|---|
| memories | No | An array of explicit memory objects to be created directly. Either this or text must be provided. | |
| text | No | The text content from which memories will be extracted. Either this or memories must be provided. | |
| text_source | No | Source of the text content. Optional. Options: "email", "social_post", "other". | |
| text_source_spec | No | Additional specification about the source. Optional. | |
| user_id | Yes | The user ID to create memories for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the creation action and two input methods, it doesn't disclose important behavioral traits like whether this is a write operation (implied but not stated), what permissions are needed, whether it's idempotent, what happens on failure, or what the return format looks like. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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, efficient sentence that clearly states the tool's purpose and two key input methods. It's front-loaded with essential information and contains no redundant or unnecessary words, making it easy to parse quickly.
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 that this is a creation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'Omi memories' are in this context, what the tool returns (e.g., success/failure, created memory IDs), or any behavioral constraints (e.g., rate limits, authentication needs). For a tool with 5 parameters and significant functionality, more context is needed to use it effectively.
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%, meaning all parameters are well-documented in the input schema itself. The description adds minimal value beyond the schema by mentioning 'extracting from text' (hinting at the 'text' parameter) and 'using explicit memory objects' (hinting at the 'memories' parameter), but doesn't provide additional semantic context like examples, edge cases, or relationships between parameters. This meets the baseline for high schema coverage.
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 the action ('creates Omi memories') and specifies two methods ('extracting from text' or 'using explicit memory objects'), which gives a good sense of what the tool does. However, it doesn't differentiate itself from sibling tools like 'create_omi_conversation' or 'read_omi_memories', leaving some ambiguity about when to use this specific memory creation tool versus other memory/conversation tools.
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 implies usage by mentioning two input methods ('extracting from text' or 'using explicit memory objects'), which provides some context for when to use it. However, it doesn't explicitly state when to choose this tool over alternatives like 'create_omi_conversation' or 'read_omi_memories', nor does it mention any prerequisites or exclusions. The guidance is present but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieves user conversations from Omi with pagination and filtering options
| Name | Required | Description | Default |
|---|---|---|---|
| include_discarded | No | Whether to include discarded conversations (default: false) | |
| limit | No | Maximum number of conversations to return (max: 1000, default: 100) | |
| offset | No | Number of conversations to skip for pagination (default: 0) | |
| statuses | No | Comma-separated list of statuses to filter conversations by | |
| user_id | Yes | The user ID to fetch conversations for |
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 'pagination and filtering options', which hints at some behavior, but fails to cover critical aspects like authentication requirements, rate limits, error handling, or what the return format looks like (e.g., JSON structure). For a retrieval tool with 5 parameters, this leaves significant gaps.
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, efficient sentence that front-loads the core purpose ('retrieves user conversations from Omi') and adds relevant details ('with pagination and filtering options'). There is no wasted verbiage, making it highly concise and well-structured.
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 the complexity of a retrieval tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on authentication, rate limits, error cases, and the structure of returned data (e.g., conversation objects). Without annotations or an output schema, the agent has insufficient information to handle this tool effectively in context.
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 the input schema fully documents all 5 parameters with descriptions. The description adds minimal value by mentioning 'pagination and filtering options', which loosely corresponds to parameters like 'limit', 'offset', and 'statuses', but doesn't provide additional semantics beyond what the schema already specifies. This meets the baseline for high schema coverage.
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 the verb ('retrieves') and resource ('user conversations from Omi'), making the purpose evident. It also mentions 'pagination and filtering options' which adds specificity. However, it doesn't explicitly distinguish this tool from its sibling 'read_omi_memories', which might cause confusion about when to retrieve conversations versus memories.
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 no guidance on when to use this tool versus alternatives like 'read_omi_memories' or 'create_omi_conversation'. It mentions filtering options but doesn't specify scenarios or prerequisites for usage, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieves user memories from Omi with pagination options
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of memories to return (max: 1000, default: 100) | |
| offset | No | Number of memories to skip for pagination (default: 0) | |
| user_id | Yes | The user ID to fetch memories for |
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 'pagination options', which adds some context about how results are handled, but it does not cover other aspects like rate limits, authentication needs, error conditions, or what the return format looks like. This leaves gaps in understanding the tool's behavior beyond basic retrieval.
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, efficient sentence that directly states the tool's function and key feature (pagination). It is front-loaded with the core purpose and avoids unnecessary words, making it highly concise and well-structured for quick comprehension.
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 the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and hints at pagination but lacks details on return values, error handling, or usage context. This leaves the agent with incomplete information for effective tool invocation, though it meets a baseline for a read operation.
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?
The input schema has 100% description coverage, documenting all three parameters (limit, offset, user_id) with details like defaults and constraints. The description adds no additional meaning beyond this, as it only mentions 'pagination options' without elaborating on parameter usage. This meets the baseline for high schema coverage but does not enhance parameter understanding.
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 the verb ('Retrieves') and resource ('user memories from Omi'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'read_omi_conversations', which might retrieve a different type of data, so it lacks sibling differentiation for 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.
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, such as when to choose it over 'read_omi_conversations' or other siblings. It mentions pagination options but does not specify scenarios or prerequisites for usage, leaving the agent without contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0create_omi_conversationcreate_omi_memoriesread_omi_conversationsread_omi_memoriesScored across 4 tools
Each tool has a clearly distinct purpose: create vs. read operations for two distinct resources (conversations and memories). The separation between conversations and memories is explicit, and the create/read distinction is unambiguous, leaving no room for confusion or misselection.
All tool names follow a consistent verb_noun pattern with 'create' or 'read' as the verb and 'omi_conversations' or 'omi_memories' as the noun. The naming is perfectly uniform, using snake_case throughout, making the set highly predictable and readable.
With 4 tools, the count is reasonable for a server focused on Omi conversations and memories. It covers create and read operations for both resources, which is well-scoped, though it might feel slightly thin if update or delete operations are expected in the domain, but it's not a significant issue.
The tool set provides create and read operations for both conversations and memories, covering basic CRUD elements. However, there are notable gaps: no update or delete tools for either resource, which could limit agent workflows if modifications or deletions are needed, making the surface incomplete for full lifecycle management.
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