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IMAGIN-studio

imagin-studio-api-docs-mcp

Official

IMAGIN.studio API Docs MCP Server

Ermöglichen Sie Ihrem KI-Programmierassistenten sofortigen Zugriff auf die vollständige IMAGIN.studio Dokumentation – CDN-Konfiguration, API-Referenzen, Integrationsleitfäden und mehr.

Ein Tool. Ein Befehl. Funktioniert mit jedem gängigen KI-Programmierassistenten.

Schnellstart

Fügen Sie dies in die MCP-Konfiguration Ihres Agenten ein:

{
  "mcpServers": {
    "imagin-docs": {
      "command": "uvx",
      "args": ["imagin-studio-api-docs-mcp"]
    }
  }
}

Oder fragen Sie einfach Ihren KI-Assistenten:

Installiere diesen MCP-Server: https://pypi.org/project/imagin-studio-api-docs-mcp/

Related MCP server: @ragrabbit/mcp

Funktionsweise

  1. Installierenuvx imagin-studio-api-docs-mcp (kein Klonen, kein venv, keine Konfiguration)

  2. Indizieren — Beim ersten Start wird die Dokumentation geklont und ein lokaler Vektor-Index erstellt (~30 Sek.)

  3. Suchen — Ihr KI-Assistent ruft search_docs auf, um relevante Dokumentation zu finden

  4. Aktuell bleiben — Der Index aktualisiert sich automatisch, wenn sich die Upstream-Dokumentation ändert

Alles läuft lokal. Keine API-Schlüssel. Keine externen Dienste.

Unterstützte Agenten

Agent

Konfigurationsort

Claude Code

.mcp.json im Projektstammverzeichnis

Claude Desktop

claude_desktop_config.json

Cursor

Einstellungen > Tools & MCP

Windsurf

~/.codeium/windsurf/mcp_config.json

VS Code + Copilot

.vscode/mcp.json

Cline

MCP-Server-Panel

Zed

~/.config/zed/settings.json

Detaillierte Einrichtungsanweisungen für jeden Agenten finden Sie im vollständigen Einrichtungsleitfaden auf PyPI.

Alternative: npx

Falls Ihr Agent uvx nicht finden kann (häufig bei GUI-Apps wie Claude Desktop und Cursor):

{
  "mcpServers": {
    "imagin-docs": {
      "command": "npx",
      "args": ["-y", "@imagin.studio/api-docs-mcp"]
    }
  }
}

Was Sie fragen können

Nach der Installation können Sie Prompts wie diese ausprobieren:

  • "Suche in der IMAGIN-Dokumentation nach CDN-Cache-Invalidierung"

  • "Wie richte ich eine benutzerdefinierte Domain mit IMAGIN ein?"

  • "Finde den API-Endpunkt für Bildtransformationen"

  • "Welche Bildformate unterstützt IMAGIN.studio?"

Pakete

Registry

Paket

Installation

PyPI

imagin-studio-api-docs-mcp

uvx imagin-studio-api-docs-mcp

npm

@imagin.studio/api-docs-mcp

npx -y @imagin.studio/api-docs-mcp

Lizenz

Apache License 2.0 – siehe LICENSE.

Available Tools

1 tool
search_docsSearch IMAGIN.studio DocumentationA
Read-onlyIdempotent

Search the official IMAGIN.studio technical documentation, integration guides, and knowledge base.

Use this tool when the user asks 'How do I...' questions, needs explanation on API concepts (CDN, referrers, caching, 360 spinner), or needs to debug integration issues. Rewrite vague queries into specific technical search terms before calling.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query. Use specific technical terms rather than vague descriptions. Good: "CDN cache invalidation headers". Bad: "caching stuff".
top_kNoNumber of results to return (1-20, default 5). Use 1-3 for focused lookups, 5 for general questions, 10-20 for broad research.

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint true, idempotentHint true, destructiveHint false. The description adds that it searches specific content types but does not discuss rate limits, authentication, or result format. It adds some context but not rich behavioral detail.

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?

Three sentences, no redundant words. First sentence states purpose, second gives usage examples, third provides query rewriting advice. Front-loaded and efficient.

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 simple read-only search tool with good annotations and output schema, the description covers when to use and what to search. It could mention authentication scope or result limitations, but overall it's reasonably complete.

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 coverage is 100% with detailed descriptions for both parameters. The description does not add per-parameter details beyond the schema, so baseline score of 3 is appropriate.

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 tool searches official IMAGIN.studio technical documentation, integration guides, and knowledge base. This is specific and complete, with no sibling tools to distinguish from.

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

Usage Guidelines5/5

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

Explicitly says when to use ('How do I' questions, API concepts, debug issues) and provides guidance to rewrite vague queries into specific terms. This is optimal usage guidance.

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. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.23
    • First observedsearch_docs

TDQS

A4.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion between different tools. The single tool is clearly described for its specific purpose.

Naming Consistency5/5

The single tool name 'search_docs' follows a consistent verb_noun pattern, which is clear and predictable.

Tool Count3/5

One tool is minimal and may feel insufficient for a documentation set; however, it might be acceptable if the scope is strictly limited to search. Still, it falls into the 'thin' category.

Completeness3/5

The tool covers the core search functionality, but lacks additional operations like retrieving a specific document or listing available topics, which could be useful for a documentation server.

Maintenance

ActivitySlowing
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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