A
licenseA
qualityD
maintenanceAn MCP server that enables analyzing and querying GitHub repositories through the GitHub Chat API, allowing users to index repositories and ask questions about their code, architecture and tech stack.
2
88
MIT
Spryker Package Search Tool
Spryker-Paketsuchtool
Ein Befehlszeilentool, das einen Model Context Protocol (MCP)-Server initialisiert, um Paketsuchfunktionen für Spryker GitHub-Repositorys bereitzustellen.
Mit diesem Tool können Sie Spryker-Pakete oder deren Codeinhalte mithilfe von Abfragen in natürlicher Sprache durchsuchen. Es unterstützt die Filterung nach bestimmten GitHub-Organisationen.
✨ Funktionen
Suche nach Spryker-Paketen auf GitHub
Suche auf Codeebene in allen Spryker-Repositories
Unterstützung für das Filtern nach Organisation (
spryker,spryker-eco,spryker-sdk,spryker-shop)Läuft als MCP-Server mit stdio-Transport
Related MCP server: Spryker Search Tool MCP Server
🚀 Installation
Stellen Sie sicher, dass npm und npx installiert sind.
git clonecd spryker-module-finder && npm installDer MCP-Server macht das Tool mit verschiedenen KI-Agenten kompatibel, um den Kontext mit dem Spryker-Projektkontext zu erweitern
Werkzeuge:
Einstellungen
Sie können so viele Server wie Projekte hinzufügen, indem Sie sie einfach mit dem Projektnamen richtig konfigurieren.
{
"mcpServers": {
"sprykerPackageSearch": {
"command": "npx",
"args": [
"-y",
"/FULL_PATH/spryker-module-finder"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN":"token"
}
}
}
}Debuggen
npx @modelcontextprotocol/inspector npx node src/index.jsPrüfen
npm testnpx eslint . --fix🧠 Verfügbare Tools
Suche nach Spryker-Paketen
Sucht nach Spryker-Paketen basierend auf einer Abfrage in natürlicher Sprache.
Parameter:
Abfrage (Zeichenfolge, erforderlich): Die Abfrage in natürlicher Sprache zum Durchsuchen von GitHub-Repositorys.
Organisationen (Array von Zeichenfolgen, optional): Liste der GitHub-Organisationen, nach denen gefiltert werden soll. Beispiel: ["spryker", "spryker-eco", "spryker-sdk", "spryker-shop"]
Suche_Spryker_Paketcode
Sucht nach PHP-Code in Spryker GitHub-Repositories.
Parameter:
Abfrage (Zeichenfolge, erforderlich): Die Abfrage in natürlicher Sprache, um im Code zu suchen.
Organisationen (Array von Zeichenfolgen, optional): Liste der GitHub-Organisationen, nach denen gefiltert werden soll. Beispiel: ["spryker", "spryker-eco", "spryker-sdk", "spryker-shop"]
Suchpfad für die Spryker-Dokumentation
Sucht nach Links zur Spryker-Dokumentation.
Parameter:
Abfrage (Zeichenfolge, erforderlich): Die Abfrage in natürlicher Sprache zum Durchsuchen der Spryker-Dokumentationslinks.
🧩 Architektur
Erstellt mit Model Context Protocol SDK
Verwendet StdioServerTransport zur Kommunikation
Validiert die Eingabe mit zod
Verwaltet die GitHub-API-Integration für die Repository- und Codesuche
📄 Lizenz
👥 Autoren
Available Tools
3 toolssearch_spryker_documentation_pathC
To search Spryker documentation path urls by query
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The natural language query to search Spryker documentation path url |
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 of behavioral disclosure. It states the tool searches documentation path URLs but doesn't describe what the search returns (e.g., list of URLs, relevance scores, pagination), how results are ranked, or any limitations (e.g., rate limits, authentication needs). This leaves critical behavioral aspects unspecified.
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 directly states the tool's function without unnecessary words. It's front-loaded with the core purpose and appropriately sized for a simple search tool, earning full marks for conciseness.
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. It doesn't explain what the tool returns (e.g., search results format), behavioral traits like search scope or limitations, or how it differs from sibling tools. For a search tool with no structured output documentation, this leaves significant gaps for an AI agent.
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 100% description coverage, with the 'query' parameter documented as 'The natural language query to search Spryker documentation path url'. The description adds no additional parameter semantics beyond what the schema provides, 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.
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: 'search Spryker documentation path urls by query'. It specifies the verb (search), resource (Spryker documentation path urls), and mechanism (by query). However, it doesn't explicitly differentiate from sibling tools like 'search_spryker_package_code' or 'search_spryker_packages', which likely search different resources.
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 sibling tools, prerequisites, or specific contexts where this search is appropriate. The agent must infer usage based on the name alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_spryker_package_codeB
To search code in Spryker GitHub repositories
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The natural language query to search in code of Spryker packages | |
| organisations | No | Optional array of organisations to filter by [`spryker`, `spryker-eco`, `spryker-sdk`, `spryker-shop` |
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. The description only says 'search code' but does not mention whether the operation is read-only, destructive, or requires specific permissions. Given the lack of annotation, this is a significant gap.
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 with no extraneous information, making it concise and easy to process.
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 simple search tool, the description barely covers the purpose but lacks essential context such as whether results are returned, the format, pagination, or any output structure. Since there is no output schema, the description should compensate, but it does not.
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 documentation coverage is 100%, with clear descriptions for both parameters (query and organisations). The description adds no additional parameter information, but per guidelines, baseline is 3 when schema coverage is high.
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 searches code in Spryker GitHub repositories, which is a specific verb-resource combination. While it doesn't explicitly distinguish from siblings, the name 'package_code' and context from sibling names imply it is for code-level search, not package metadata or documentation.
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 is provided on when to use this tool versus alternatives like search_spryker_packages or search_spryker_documentation. The description only states the purpose without explaining how it differs or when to prefer it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_spryker_packagesB
To search the Spryker package repository in Github
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The natural language query to search in Github | |
| organisations | No | Optional array of organisations to filter by [`spryker`, `spryker-eco`, `spryker-sdk`, `spryker-shop` |
TDQS
B3.2/5.0
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. It only states the purpose without disclosing behavioral traits such as read-only nature, rate limits, or authentication needs. The tool is essentially a black box.
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, well-formed sentence that front-loads the purpose. It is concise with zero wasted words.
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?
Despite having only 2 parameters with full schema coverage, the description lacks details about return format, error handling, or prerequisites. For a search tool with siblings, more context on scope and output would be helpful.
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 baseline is 3. The description does not add any additional parameter meaning beyond what the schema already provides.
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 'To search the Spryker package repository in Github' clearly states the verb (search) and resource (Spryker package repository), and it distinguishes from sibling tools that search code or documentation.
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 like search_spryker_package_code or search_spryker_documentation. No when-not-to-use or context hints.
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.
3 tool updates
- First observed
search_spryker_documentation_path - First observed
search_spryker_package_code - First observed
search_spryker_packages
TDQS
B3.2/5.0
Scored across 3 tools
Disambiguation4/5
The three tools have distinct primary targets: documentation paths, package code, and package repository search. However, 'search_spryker_package_code' and 'search_spryker_packages' could be slightly confusing as both involve GitHub repositories, though their descriptions clarify one searches code within repositories and the other searches the package repository itself.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with the verb 'search' followed by a specific noun phrase (spryker_documentation_path, spryker_package_code, spryker_packages). This uniformity makes the tool set predictable and easy to understand.
Tool Count3/5
With only 3 tools, the server feels thin for a 'Package Search Tool' that might imply broader functionality like installing or managing packages. While the tools cover key search aspects, the limited count may restrict agent workflows, especially if additional operations like package installation or version checking are needed.
Completeness3/5
The tools provide search capabilities across documentation, code, and packages, which aligns with the server's name. However, there are notable gaps: no tools for actions like installing packages, checking package versions, or managing dependencies, which are common in package management contexts. This limits the server to read-only search operations.
Maintenance
ActivityInactive
ResponsivenessNo issues
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