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tewfiq
by tewfiq

genai-solutions-mcp

一个MCP服务器,暴露了一个精心整理的生成式AI工具数据库—— 自2023年以来我在Notion中维护的1,197条记录——作为四个工具供AI助手直接查询。

与其让模型猜测存在哪些AI工具并得到一个看似合理但过时的答案, 不如让它搜索一个背后有真人维护的数据集。

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

安装

npm install
npm run build
npm start

无需API密钥、无需网络、无需数据库。数据集随仓库一起提供。

将其注册到MCP客户端(此处以Claude Desktop为例):

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

Related MCP server: disvr

工具

工具

用途

search_solutions

自由文本+筛选条件(类型、生态系统、能力、来源、精选)

get_solution

根据ID获取完整记录

list_categories

每个类别及其记录数量

compare_solutions

2–4条记录在相同字段上对齐比较

设计决策

一个提交的快照,而非实时的Notion代理。 显而易见的设计是在每次工具调用时调用Notion API。但这也使得该仓库对除我之外的任何人都毫无用处:你需要我的令牌和我的数据库。相反,scripts/sync-notion.ts 将Notion导出为 data/solutions.json,该文件在此处进行版本管理,服务器仅读取该文件。这种权衡在于数据新鲜度——数据与上次同步时一样新——而服务器任何人都可以在十五秒内克隆并运行,无需凭证、无运行时网络依赖、无速率限制。底层数据最多每周变化一次,因此新鲜度是较容易放弃的一环。

子串搜索,而非嵌入。 约1,100条记录是一个亚毫秒级的线性扫描。向量索引会增加同步时的嵌入步骤、模型依赖性、非确定性结果以及与快照保持一致的索引——而在这个语料库中,有用的查询大多是名称和类别,额外带来的语义回忆收益有限。如果数据集增长一个数量级或摘要变得更长,这是首先需要重新考虑的问题。

搜索返回投影而非完整记录。 search_solutions 仅返回id、名称、类型和URL。对于20条结果的查询返回完整记录会消耗大量代理上下文在通常不需要的字段上;当需要完整记录时,可以使用 get_solution。

同步时使用属性白名单而非黑名单。 Notion数据库包含不应公开的内部工作流状态和附件。scripts/sync-notion.ts 明确列出它导出的属性,因此稍后在Notion中添加私有列不会悄然泄露到这里。

已知限制

  • Notion的 Type 是单选字段,因此每个工具只有一个类别,即使适合两个类别也是如此。

  • 类别值是在三年内手动输入的,且不一致;同步功能会折叠大小写重复项,但不会合并近义词。

  • 没有基于字段加权子串匹配之外的相关性排序。

  • 属性标签不一致。Local 和 Open Source 是在不同时期以不同习惯应用的,它们仅在一条记录上重叠,而实际上许多工具都符合这两个条件。筛选结果如实反映标记情况,而非实际情况——此数据集与大多数真实内部数据库共享此特性。

  • Node解析取决于宿主环境。根据启动上下文,该服务器在同一台机器上曾在两个不同的Node安装下启动。如果这对你很重要,请在客户端配置中固定运行时路径。

同步(仅维护者)

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

许可证

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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