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MCP server · Content

Agentic AI Tool Suite

A suite of Model Context Protocol (MCP) servers designed to enhance AI agent capabilities. Provides tools for media search/understanding (images, video), web information retrieval, PDF generation, and PowerPoint presentation creation, enabling agents to interact with diverse data formats and external resources

Unclaimed last commit 11 months ago content
48Fair

Scored 5 months ago · breakdown

About Agentic AI Tool Suite

Agentic AI Tool Suite is an MCP server published by Godzilla675 in the Content category: a suite of Model Context Protocol (MCP) servers designed to enhance AI agent capabilities. Provides tools for media search/understanding (images, video), web information retrieval, PDF generation, and PowerPoint presentation creation, enabling agents to interact with diverse data formats and external resources.

The repository has 20 stars and 3 forks, with the last commit 11 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/Godzilla675/agentic-ai-tool-suite

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 4 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • !License declaredNo license file. Legally you have no right to use it in a product.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

MseeP.ai Security Assessment Badge

Unified MCP Suite

This repository contains a collection of Model Context Protocol (MCP) servers, packaged together for convenience. Each server provides distinct functionalities related to media handling, information retrieval, and document creation.

📦 View Published Packages - Easy installation guide for all npm packages!

Important: These servers are designed to run as separate processes. You need to set up and configure each server individually within your MCP client (e.g., Cline or the Claude Desktop App).

Included Servers

  • Media Tools Server (media-tools-server): Provides tools for searching images (Unsplash) and videos (YouTube), downloading images, and understanding image/video content (Google Gemini, YouTube Transcripts). (Node.js/TypeScript)
  • Information Retrieval Server (information-retrieval-server): Provides tools for performing web searches (Google Custom Search) and crawling web pages. (Node.js/TypeScript)
  • PDF Creator Server (pdf-creator-server): Provides a tool to generate PDF documents from HTML content using Playwright and Pillow. (Python)
  • Presentation Creator Server (presentation-creator-server): Provides tools to assemble PowerPoint presentations from HTML slide content and generate PDFs from HTML. (Python)

Quick Start (Recommended)

The easiest way to use these MCP servers is via npm packages. No need to clone or build!

Published Packages

All TypeScript/Node.js servers are now available on npm:

  • information-retrieval-mcp-server: Web search and crawling
  • media-tools-mcp-server: Image/video search and media understanding
  • presentation-creator-mcp-server: Create presentations and PDFs from HTML

Installation Options

Option 1: Using npx (Easiest - No Installation Required)

Add to your MCP client config (e.g., claude_desktop_config.json):

Location of config file:

  • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "information-retrieval": {
      "command": "npx",
      "args": ["-y", "information-retrieval-mcp-server"],
      "env": {
        "GOOGLE_API_KEY": "your-google-api-key",
        "GOOGLE_CSE_ID": "your-custom-search-engine-id"
      }
    },
    "media-tools": {
      "command": "npx",
      "args": ["-y", "media-tools-mcp-server"],
      "env": {
        "UNSPLASH_ACCESS_KEY": "your-unsplash-key",
        "GEMINI_API_KEY": "your-gemini-key"
      }
    },
    "presentation-creator": {
      "command": "npx",
      "args": ["-y", "presentation-creator-mcp-server"]
    }
  }
}

API Keys Required:

  • Information Retrieval Server:
  • Media Tools Server:
  • Presentation Creator Server: No API keys required

Option 2: Global npm Installation

npm install -g information-retrieval-mcp-server
npm install -g media-tools-mcp-server
npm install -g presentation-creator-mcp-server

Then configure with just the command name:

{
  "mcpServers": {
    "information-retrieval": {
      "command": "information-retrieval-mcp-server",
      "env": { /* ... */ }
    }
  }
}

Advanced Setup (Build from Source)

If you prefer to build from source or need to modify the servers:

1. Clone the Repository

git clone <repository-url> # Replace <repository-url> with the actual URL
cd unified-mcp-suite

2. Media Tools Server (media-tools-server)

(Node.js/TypeScript)

a. Navigate to Directory:

cd media-tools-server

b. Install Dependencies:

npm install

c. Build the Server:

npm run build

(This compiles the TypeScript code into JavaScript in the build directory.)

d. Obtain API Keys:

  • Unsplash API Key: Required for image search. Create an account and register an application at https://unsplash.com/developers.
  • Google API Key: Required for video search/understanding and image understanding.
    • Enable the "YouTube Data API v3" and "Vertex AI API" (for Gemini) in your Google Cloud Console project: https://console.cloud.google.com/
    • Create an API key under "APIs & Services" -> "Credentials". Restrict the key if necessary.

e. Configure MCP Client:

Add the following configuration to your MCP client's settings file (e.g., cline_mcp_settings.json or claude_desktop_config.json). Replace placeholders with your actual API keys and the correct absolute path to the built server file.

{
  "mcpServers": {
    // ... other servers
    "media-tools": {
      "command": "node",
      "args": ["C:/path/to/unified-mcp-suite/media-tools-server/build/index.js"], // <-- UPDATE THIS PATH
      "env": {
        "UNSPLASH_ACCESS_KEY": "YOUR_UNSPLASH_API_KEY", // <-- ADD YOUR KEY
        "GOOGLE_API_KEY": "YOUR_GOOGLE_API_KEY"       // <-- ADD YOUR KEY
      },
      "disabled": false, // Set to false to enable
      "autoApprove": []
    }
    // ... other servers
  }
}

f. Navigate Back:

cd ..

3. Information Retrieval Server (information-retrieval-server)

(Node.js/TypeScript)

a. Navigate to Directory:

cd information-retrieval-server

b. Install Dependencies:

npm install

c. Build the Server:

npm run build

d. Obtain API Keys:

e. Configure MCP Client:

Add the following configuration to your MCP client's settings file. Replace placeholders with your actual API key, Search Engine ID, and the correct absolute path.

{
  "mcpServers": {
    // ... other servers
    "information-retrieval": {
      "command": "node",
      "args": ["C:/path/to/unified-mcp-suite/information-retrieval-server/build/index.js"], // <-- UPDATE THIS PATH
      "env": {
        "GOOGLE_API_KEY": "YOUR_GOOGLE_API_KEY",             // <-- ADD YOUR KEY
        "GOOGLE_CSE_ID": "YOUR_CUSTOM_SEARCH_ENGINE_ID"  // <-- ADD YOUR ID
      },
      "disabled": false, // Set to false to enable
      "autoApprove": []
    }
    // ... other servers
  }
}

f. Navigate Back:

cd ..

4. PDF Creator Server (pdf-creator-server)

(Python)

a. Navigate to Directory:

cd pdf-creator-server

b. Create and Activate Virtual Environment:

# Create environment
python -m venv .venv

# Activate environment
# Windows (Command Prompt/PowerShell)
.\.venv\Scripts\activate
# macOS/Linux (bash/zsh)
# source .venv/bin/activate

c. Install Dependencies:

pip install -r requirements.txt

d. Install Playwright Browsers: (Required for PDF generation)

playwright install

e. Configure MCP Client:

Add the following configuration to your MCP client's settings file. Replace the placeholder with the correct absolute path to the Python executable within the virtual environment and the server script.

{
  "mcpServers": {
    // ... other servers
    "pdf-creator": {
      // UPDATE python path to point to the .venv executable
      "command": "C:/path/to/unified-mcp-suite/pdf-creator-server/.venv/Scripts/python.exe", // Windows example
      // "command": "/path/to/unified-mcp-suite/pdf-creator-server/.venv/bin/python", // macOS/Linux example
      "args": ["C:/path/to/unified-mcp-suite/pdf-creator-server/pdf_creator_server.py"], // <-- UPDATE THIS PATH
      "env": {}, // No specific environment variables needed by default
      "disabled": false, // Set to false to enable
      "autoApprove": []
    }
    // ... other servers
  }
}

f. Deactivate Virtual Environment (Optional):

deactivate

g. Navigate Back:

cd ..

5. Presentation Creator Server (presentation-creator-server)

(Python)

a. Navigate to Directory:

cd presentation-creator-server

b. Create and Activate Virtual Environment:

# Create environment
python -m venv .venv

# Activate environment
# Windows (Command Prompt/PowerShell)
.\.venv\Scripts\activate
# macOS/Linux (bash/zsh)
# source .venv/bin/activate

c. Install Dependencies:

pip install -r requirements.txt

d. Install Playwright Browsers: (Required for screenshotting HTML slides)

playwright install

e. Configure MCP Client:

Add the following configuration to your MCP client's settings file. Replace the placeholder with the correct absolute path to the Python executable within the virtual environment and the server script.

{
  "mcpServers": {
    // ... other servers
    "presentation-creator": {
      // UPDATE python path to point to the .venv executable
      "command": "C:/path/to/unified-mcp-suite/presentation-creator-server/.venv/Scripts/python.exe", // Windows example
      // "command": "/path/to/unified-mcp-suite/presentation-creator-server/.venv/bin/python", // macOS/Linux example
      "args": ["C:/path/to/unified-mcp-suite/presentation-creator-server/presentation_creator_server.py"], // <-- UPDATE THIS PATH
      "env": {}, // No specific environment variables needed by default
      "disabled": false, // Set to false to enable
      "autoApprove": []
    }
    // ... other servers
  }
}

f. Deactivate Virtual Environment (Optional):

deactivate

g. Navigate Back:

cd ..

Running the Servers

Once configured in your MCP client, the servers should start automatically when the client launches. You can then use the tools provided by each server through your MCP client interface.

Example Configuration File

An example configuration file, example_cline_mcp_settings.json, is included in the root of this repository. You can use this as a template for configuring the servers in your MCP client (like Cline).

To use the example:

  1. Locate your MCP client's actual settings file (e.g., c:\Users\YourUser\AppData\Roaming\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json for Cline in VS Code on Windows).
  2. Copy the server configurations from example_cline_mcp_settings.json into your actual settings file, merging them with any existing server configurations you might have.
  3. Crucially, update all placeholder paths (e.g., C:/absolute/path/to/...) to reflect the actual absolute path where you cloned the unified-mcp-suite repository on your system.
  4. Replace all placeholder API keys (e.g., YOUR_GOOGLE_API_KEY_HERE) with your own keys obtained during the setup steps.
  5. Ensure the command path for the Python servers correctly points to the python.exe (Windows) or python (macOS/Linux) executable inside the respective .venv directory you created.

README fetched from the repository 4 days ago. The original is authoritative.

Questions

About Agentic AI Tool Suite

How do I install Agentic AI Tool Suite?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Agentic AI Tool Suite safe to use with an AI agent?

Its trust score is 48 out of 100 (fair). It passes 3 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Agentic AI Tool Suite still maintained?

The last commit was 11 months ago and 1 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.