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genai-solutions-mcp

생성형 AI 도구의 선별된 데이터베이스를 제공하는 MCP 서버입니다 — 2023년부터 제가 Notion에서 관리해 온 1,197개의 레코드를 AI 어시스턴트가 직접 쿼리할 수 있는 네 가지 도구로 노출합니다.

모델에게 어떤 AI 도구가 있는지 물어보고 그럴듯하지만 오래된 답변을 얻는 대신, 그 뒤에 사람이 있는 데이터셋을 검색하도록 요청합니다.

> Which open-source tools in here run locally and have a CLI?
> Compare Firecrawl and the other scraping options.

설치

npm install
npm run build
npm start

API 키, 네트워크, 데이터베이스가 필요 없습니다. 데이터셋은 저장소와 함께 제공됩니다.

MCP 클라이언트(여기서는 Claude Desktop)에 등록하세요:

{
  "mcpServers": {
    "genai-solutions": {
      "command": "node",
      "args": ["/absolute/path/to/genai-solutions-mcp/dist/src/index.js"]
    }
  }
}

Related MCP server: disvr

도구

도구

용도

search_solutions

자유 텍스트 + 필터(유형, 생태계, 기능, 출처, 추천)

get_solution

하나의 ID에 대한 전체 레코드

list_categories

레코드 수가 포함된 모든 카테고리

compare_solutions

동일한 필드에 정렬된 2–4개 레코드

설계 결정

실시간 Notion 프록시가 아닌 커밋된 스냅샷. 명백한 설계는 모든 도구 호출에서 Notion API를 호출하는 것입니다. 그것은 또한 저장소를 나 외에는 모두에게 쓸모없게 만드는 설계이기도 합니다. 당신은 내 토큰과 내 데이터베이스가 필요할 것이기 때문입니다. 대신 scripts/sync-notion.ts는 Notion을 data/solutions.json으로 내보내며, 이 파일은 여기에서 버전 관리되고 서버는 그 파일만 읽습니다. 트레이드오프는 신선도 — 데이터는 마지막 동기화 시점만큼 최신입니다 — 와 자격 증명, 호출 시 네트워크 의존성, 속도 제한 없이 누구나 15초 안에 클론하고 실행할 수 있는 서버 사이입니다. 기본 데이터는 기껏해야 주 단위로 변경되므로 신선도를 포기하는 것이 더 저렴한 선택입니다.

임베딩이 아닌 부분 문자열 검색. 약 1,100개의 레코드는 서브 밀리초 선형 스캔입니다. 벡터 인덱스는 동기화에 임베딩 단계, 모델 의존성, 비결정적 결과, 스냅샷과 일관성을 유지해야 하는 인덱스를 추가할 것입니다 — 유용한 쿼리가 대부분 이름과 카테고리인 코퍼스에서 의미론적 검색을 얻는 대가로 말입니다. 데이터셋이 한 자릿수 이상 커지거나 요약이 길어지면, 이것이 가장 먼저 재검토할 사항입니다.

검색은 전체 레코드가 아닌 프로젝션을 반환합니다. search_solutions는 id, name, type, url만 반환합니다. 20개 결과 쿼리에 대해 전체 레코드를 반환하면 에이전트의 컨텍스트 중 많은 부분을 일반적으로 필요하지 않은 필드에 소비하게 됩니다. get_solution은 필요할 때 사용할 수 있습니다.

동기화의 속성 화이트리스트, 블랙리스트가 아닙니다. Notion 데이터베이스에는 공개되어서는 안 되는 내부 워크플로 상태와 첨부 파일이 포함되어 있습니다. scripts/sync-notion.ts는 내보내는 속성을 명명하므로 나중에 Notion에서 비공개 열을 추가해도 여기서 조용히 유출될 수 없습니다.

알려진 제한 사항

  • Notion의 Type은 단일 선택이므로 각 도구는 두 개가 적합하더라도 정확히 하나의 카테고리를 갖습니다.

  • 카테고리 값은 3년에 걸쳐 수동으로 입력되었으며 불균일합니다. 동기화는 대소문자 중복을 접지만 유사어를 병합하지는 않습니다.

  • 필드 가중치 부분 문자열 매칭 이상의 관련성 순위는 없습니다.

  • 속성 태깅이 불균일합니다. Local과 Open Source는 서로 다른 시기에 서로 다른 습관으로 적용되었으며, 많은 도구가 둘 다에 해당함에도 불구하고 하나의 레코드에서만 겹칩니다. 필터는 무엇이 사실인지가 아니라 무엇이 태그되었는지에 대해 정직합니다 — 이 속성은 대부분의 실제 내부 데이터베이스와 공유하는 특성입니다.

  • Node 해석은 호스트 환경에 따라 다릅니다. 서버는 실행 컨텍스트에 따라 같은 머신에서 두 개의 다른 Node 설치로 시작되는 것이 관찰되었습니다. 이것이 중요하다면 클라이언트 구성에서 런타임 경로를 고정하세요.

동기화(관리자 전용)

NOTION_TOKEN=… NOTION_DATABASE_ID=… npm run sync
git diff data/solutions.json   # read it before committing

라이선스

MIT

Available Tools

4 tools
compare_solutionsCompare solutionsB

Return 2 to 4 solutions side by side on the same fields.

ParametersJSON Schema
NameRequiredDescriptionDefault
idsYes

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of disclosing behavioral traits. The description only mentions returning solutions side by side, but does not state whether this tool is read-only, any side effects, or constraints like required permissions. It lacks transparency beyond the basic function.

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 concise sentence that uses active voice and front-loads the key information (return 2 to 4 solutions). No unnecessary words.

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?

Given that there is no output schema and no annotations, the description is minimal. It tells what the tool does and the range of solutions, but does not describe the output format, any sorting or ordering, or related constraints like required fields for comparison. It is adequate but incomplete.

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 schema describes the only parameter 'ids' with min/max items, but the description adds context that the output is a side-by-side comparison on the same fields. Since schema coverage is 0%, the description partially compensates by explaining the purpose, but does not elaborate on the 'ids' parameter meaning or format.

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 returns 2 to 4 solutions side by side on the same fields, which provides a specific verb ('return') and resource ('solutions'). It distinguishes from siblings like 'search_solutions' or 'get_solution' by emphasizing comparison.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that this tool is for comparing multiple solutions, but it does not provide explicit guidance on when to use it versus alternatives like 'get_solution' or 'search_solutions'. No when-not-to-use or exclusion criteria are mentioned.

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

get_solutionGet one solutionA

Return the full record for a single solution by id.

ParametersJSON Schema
NameRequiredDescriptionDefault
idYes

TDQS

A3.7/5.0
Behavior3/5

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

Since no annotations are provided, the description bears the full burden of behavioral disclosure. It confirms a read operation ('Return the full record') without indicating idempotency, rate limits, or error behavior. It does not state whether the returned record is guaranteed fresh or cached, nor whether authentication is needed. This is adequate but minimal.

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 sentence (14 words) that efficiently captures purpose, resource, and method. Every word is relevant. No wasted phrasing. Front-loaded with the action 'Return the full record' – ideal for scanning.

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?

Given the tool's simplicity (1 required param, no nested objects, no output schema, no annotations), the description provides sufficient functional purpose. However, it lacks mention of what happens if the id is invalid (e.g., 404), or whether the response includes nested objects like related items. The absence of an output schema means the description should hint at the 'full record' structure, but it does not enumerate fields. It is just adequate for a simple retrieval tool.

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%, meaning the description must compensate. The description mentions 'by id,' which maps to the required 'id' parameter, adding basic context. However, it does not clarify that id is a string (schema indicates type), nor does it provide format guidance (e.g., UUID vs plain string). For a single required param, this is borderline acceptable but lacks helpful detail beyond the schema.

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 'Return the full record for a single solution by id,' specifying the verb (return) and resource (full record for solution) and the identifying method (by id). It distinguishes from list_categories and search_solutions (which retrieve multiple) and compare_solutions (comparison), but could be more explicit that this is the singular retrieval endpoint.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when you need a complete record of a known solution, contrasting with search_solutions (which returns summaries/partial data) and list_categories (which returns categories, not solutions). However, no explicit 'when not to use' guidance is given, though the sibling context clarifies alternatives. The lack of mention about requiring the ID beforehand is a minor gap.

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

list_categoriesList categoriesA

Return every category present in the database with its record count, so filters can be built against real values rather than guesses.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.3/5.0
Behavior4/5

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 discloses that the tool returns every category with its record count, which is a clear behavioral trait. It does not mention performance, data freshness, or side effects, but for a simple read-only list tool, the description is adequate.

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 sentence that is front-loaded with the key action ('Return every category') and includes the purpose. Every word earns its place with no wasted content.

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?

Given no parameters, no output schema, and no annotations, the description is relatively complete for a simple list tool. However, it could be improved by mentioning the response format (e.g., whether categories are sorted) or any limits. The explanation of purpose is helpful, but the lack of output schema details leaves some ambiguity.

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

Parameters4/5

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

There are no parameters, so schema description coverage is trivially 100%. The description adds no parameter information, but with zero parameters, a baseline score of 4 is appropriate as the description already provides value beyond the schema.

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 states 'Return every category' with a specific verb and resource, and explains the purpose ('so filters can be built against real values rather than guesses'). This clearly distinguishes it from sibling tools which deal with solutions, not categories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool: when building filters based on real category values. It provides context but does not explicitly exclude alternatives or state when not to use it. However, siblings are clearly different (solutions), so the guidance is sufficient.

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

search_solutionsSearch GenAI solutionsA

Search a curated database of generative AI tools by free text and filters. Returns a short projection (id, name, type, url); call get_solution with an id for the full record.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeNoCategory — call list_categories for valid values
limitNoDefault 20, max 100
queryNoFree text, matched against name
originNoAll must match. E.g. France, EMEA, China, YC
ecosystemNo
picksOnlyNoRestrict to curator's picks
capabilitiesNoAll must match. E.g. API, Open Source, Local, Terminal, Installation, HF

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description takes on the full burden of behavioral disclosure. It explains the return shape (short projection) and directs to get_solution for full records. However, it omits behavioral traits such as read-only nature, rate limits, authentication requirements, pagination behavior (though limit param exists), result ordering, or what happens with empty results. This is a moderate disclosure but has gaps.

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?

Two sentences front-load the action and result, then provide a clear pointer to the sibling tool. Every sentence serves a distinct purpose, with no fluff or repetition. Ideal conciseness for a search tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 optional parameters, no required fields, and no output schema, the description covers the main input mechanism (free text and filters), the output projection, and the follow-up sibling call. However, it does not explain the overall filtering logic (AND across parameters) or pagination, which are implicit from the limit parameter. Still, it is reasonably complete for standard usage.

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 high (86%), so the schema already provides strong param documentation. The description adds no additional parameter-level information beyond the schema (e.g., it doesn't explain how multiple filters combine or the meaning of limit's default). Given the high baseline, the description's value is neutral; it doesn't degrade but doesn't enhance.

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 verb 'Search' and the resource 'curated database of generative AI tools', and specifies the method 'by free text and filters'. It distinguishes itself from siblings by mentioning 'returns a short projection (id, name, type, url); call get_solution...' and implicitly from list_categories (for valid values of type) and compare_solutions (not mentioned but different purpose).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells the agent when to use get_solution ('for the full record') after a search, which provides a clear alternative. However, it does not explicitly state when to avoid search_solutions or when to use list_categories or compare_solutions, leaving some ambiguity for related sibling tools.

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. 4 tool updatesv0.1.0
    • First observedcompare_solutions
    • First observedget_solution
    • First observedlist_categories
    • First observedsearch_solutions

TDQS

A4/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: search for filtering, get for full details, list categories for filter options, and compare for side-by-side comparison. No overlap exists.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (search_solutions, get_solution, list_categories, compare_solutions), making them predictable and easy to understand.

Tool Count5/5

With four tools, the server is well-scoped for a curated database of generative AI solutions. Each tool earns its place, covering search, retrieval, category listing, and comparison without unnecessary bloat.

Completeness5/5

The tool set covers the core read-only operations needed for a solutions database: discovery (search), detail retrieval (get), filter exploration (list_categories), and comparison. No obvious gaps—the domain is fully addressed.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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