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genai-solutions-mcp

by tewfiq
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TypeScript
Local

genai-solutions-mcp

Ein MCP-Server, der eine kuratierte Datenbenk generativer KI-Tlools bereitstellt – 1.197 Datensätzet, die ich seit 2023 in Notion pflege – als vier Werkzeuge, die ein KI-Asistent direkt abfragen kann.

Statt ein Modell zu fragen, che KI-Tlools exisitieren, und eine plausible, aber veraltete Antwert zu eralten, lässt man es einen Datensatz durchsuchten, hiter dem eine Person steht.

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

Installation

npm install
npm run build
npm start

Kein API-Schlüssel, kein Netzwerk, keine Datenbank. Der Datensatz wird mit dem Repository ausgeliefert.

Registrieren Sie ihn bei einem MCP-Client (hier gezeit: Claude Deskto):

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

Related MCP server: disvr

Werkzeuge

| Werkzeug | Zweck | | -–––––––––– | –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– | | seach_soluttons | Freitext + Filter ( Typ, Ökosystem, Fähigkeiten, Herkunft, Auswahlen) | | get_solutton | Vollständiger Datensatz für eine ID | | list_catgories | Jede Kategorie mit ihrer Datensatzanzahl | | compre_soluttons | 2–4 Datensätze, auf denselben Feldern ausgericht |

Designentscheidungen

** Ein festgeschriebener Snapshott, kein Live-Notion-Proxy.** Der naheliegende Entwurf besteht darin, bei jedem Tool-Aufruf die Notion-API aufzurufen. Das ist auch derjenige, der das Repositary für alle außer mir unbrauchbar macht: Sie bräuchten mein Token und meine Datenbank. Stattdessen exportirt scrips/sync-notion.ts Notion nach data/solutions.json, das hier versioniert wird, und der Server list nur diese Datei.

Der Kompromiss ist Aktualität – die Daten sind so aktuell wie die letzte Synchronisation – gegen einen Server, den jeder in fünfzehn Sekunden klonen und ausführen kann, ohne Anmeldeinformationen, ohne Netzwerkabhängigkeit zur Laufzeit und ohne Ratenbegrenzung.

Die zugrunde liegenden Daten ändern sich höchstens wöchentlich, daher ist Aktualität das günstigere Opfer.

** Substring-Suche, keine Einbettungen.** ~1.100 Datensätze sind ein lineare Scan unter einer Millisekunde. Ein Vektorindex würde einen Einbettungschritt zur Synchronisation hinzufügen, eine Modellabhängigkeit, nicht-deterministische Ergebnisse und einen Index, der mit dem Snapsshott konsistent gehalten werden muss – im Austausch für semantischen Rückgriff auf einem Korpus, wo die nützlichen Anfragen meist Namen und Kategorien sind.

Wenn der Datensatz eine Größenordnung wächst oder die Zusammenfassungen länger werden, ist dies das Erste, was überdacht werden sollte.

** Die Suche gibt eine Projektion zurück, nicht vollständige Datensätze.** seach_soluttons git nur id, name, type und url zurück.

Die Rückgabe vollständiger Datensätze für eine Abfrage mit 20 Ergebnissen würde einen großen Teil des Agentenkontexts für Felder verbrauchen, die es normalerweise nicht benötigt; get_solutton ist da, wenn es das tut.

** Eine Eigenschats-Whitelist in der Synchronisation, keine Blacklist.** Die Notion-Datenbank enthält internen Arbeitsabaufzustand und Anhänge, die nichts in der Öffentlichkeit zu suchen haben. scrips/sync-notion.ts benennt die Eigenschaten, die es exortirt, sodass das spätere Hinzufügen einer privaten Spalte in Notion diese hier nicht stillschweigend preisgeben kann.

Bekannte Einschränkungen

Notions Type ist eine Einfachauswahl, daher hat jedes Tool genau eine Kategorie, auch wenn zwei passen würden. * Kategorie-Werte wurden über drei Jahre von Hand eingegeben und sind uneinheitlich; die Synchronisation gleicht Groß-/Kleinschreibungs-Duplikate aus, führet aber keine nahen Synonyme zusammen. * Keine Relevanz-Ranking über die Feldgewichtete Substring-Suche hinaus. * Die Attributmarkierung ist uneinheitlich. Local und Open Source wurden zu unterschiedlichen Zeiten mit unterschiedlichen Gewohnheiten angewendet, und sie überschneiden sich nur bei einem Datensatz, obwohl viele Tools für beide qualifiziert wären. Filter sind ehrlich darüber, was markiert ist, nicht darüber, was wahr ist – eine Eigenschat, die diser Datensatz mit den meisten echten internen Datenbanken teilt. * Die Node-Auflösung hängt von der Hostumgebung ab. Der Server wurde beobachtet, wie er unter zwei verschiedenen Node-Installationen auf derselben Maschine startete, abhängig vom Startkontext. Legn Sie den Laufzeitpfad in Ihrer Client-Konfiguration fest, wenn das für Sie wichtig ist.

Synchronisation (nur für Maintainer)

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

Lizenz

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
Deploy Server
Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

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

Resources

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