fmcp-trial-atharva 1.1.0

FluidMCP - Universal MCP server launcher and remote client (Trial Version)

FluidMCP CLI

A powerful command-line interface for managing and running MCP (Model Context Protocol) servers. FluidMCP CLI allows you to install, configure, and run MCP packages from the FluidMCP registry with ease.

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Features

• 🚀 Install MCP packages from the FluidMCP registry
• 🔧 Interactive environment variable configuration
• 🌐 Run individual or multiple MCP servers
• 🔒 Secure mode with bearer token authentication
• ☁️ S3-based configuration management
• 📁 Local and remote configuration file support
• 🎯 Automatic port management and conflict resolution

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Installation

pip install fluidmcp

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Quick Start

Install a package:

fluidmcp install author/package@version

List installed packages:

fluidmcp list

Run a package:

fluidmcp run package --port --start-server

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Commands

install

Install MCP packages from the FluidMCP registry.

fluidmcp install <author/package@version> [--master]

Examples:

# Install a specific version
fluidmcp install Perplexity/perplexity-ask@1.0.0

# Install latest version
fluidmcp install Perplexity/perplexity-ask

# Install with master env file (skips API key prompts)
fluidmcp install Perplexity/perplexity-ask --master

Options:

• --master: Use master environment file for API keys (skips interactive prompts)

Package Format:

• author/package@version - Install specific version
• author/package - Install latest version

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run

Run MCP servers from installed packages or configuration files.

fluidmcp run <package|all|file> [options]

Examples:

# Run a specific package with FastAPI client server
fluidmcp run Airbnb/airbnb@0.1.0 --port 8200 --start-server

# Run all installed packages
fluidmcp run all

# Run with master S3 configuration
fluidmcp run all --master

# Run from local configuration file
fluidmcp run <path-to-your-directory>config.json --file

# Run from S3 presigned URL
fluidmcp run https://s3.amazonaws.com/bucket/config.json --s3

# Run with secure mode and custom token
fluidmcp run Fluid_Ai/jupyter@1.0.0 --secure your-bearer-token --port 8200 --start-server

Options:

• --port <number>: Specify port for SuperGateway (default: 8111)
• --start-server: Start FastAPI client server
• --force-reload: Force reload by killing existing processes without prompt
• --master: Use master metadata file from S3
• --secure: Enable secure mode with bearer token authentication
• --token <token>: Bearer token for secure mode (auto-generated if not provided)
• --file: Treat package argument as path to local JSON configuration file
• --s3: Treat package argument as S3 presigned URL to configuration file

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list

Display all installed MCP packages.

fluidmcp list

Output format:

Installation directory: /path/to/.fmcp-packages
author1/package1@1.0.0
author2/package2@2.1.0

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edit-env

Interactively edit environment variables for installed packages.

fluidmcp edit-env <authorname/package@version>

Example:

# Edit environment variables for a specific package
fluidmcp edit-env Fluid_Ai/jupyter@1.0.0

Features:

• Interactive environment variable editor
• Secure masking of API keys and sensitive data
• Support for both structured and simple environment formats
• Real-time validation and updates

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Configuration

Environment Variables

FluidMCP CLI uses several environment variables for configuration:

# S3 Configuration (for --master mode)
export S3_BUCKET_NAME="your-bucket"
export S3_ACCESS_KEY="your-access-key"
export S3_SECRET_KEY="your-secret-key"
export S3_REGION="us-east-1"

# Registry configuration
export MCP_FETCH_URL="https://registry.fluidmcp.com/fetch-mcp-package"
export MCP_TOKEN="your-registry-token"

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Package Structure

Installed packages follow this directory structure:

.fmcp-packages/
├── author1/
│   └── package1/
│       └── 1.0.0/
│           ├── metadata.json
│           └── [package files]
└── author2/
    └── package2/
        └── 2.1.0/
            ├── metadata.json
            └── [package files]

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Metadata Format

Each package contains a metadata.json file:

{
  "mcpServers": {
    "package-name": {
      "command": "npx",
      "args": ["-y", "@package/server"],
      "env": {
        "API_KEY": "value"
      }
    }
  }
}

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S3 Files

For S3 operations, you can use following Json format:

{
  "mcpServers": {
    "server1": {
      "command": "npx",
      "args": ["-y", "example-package@1.0.0"],
      "env": {
        "API_KEY": "your-api-key"
      },
      "port": "8100",
      "install_path": "/path/to/.fmcp-packages/Author/package/1.0.0",
      "fmcp_package": "Author/package@1.0.0"
    },
    "server2": {
      "command": "uvx",
      "args": ["another-server"],
      "env": {
        "TOKEN": "value"
      },
      "port": "8101",
      "install_path": "/path/to/.fmcp-packages/Author/another-package/2.0.0",
      "fmcp_package": "Author/another-package@2.0.0"
    }
  }
}

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Trying out an MCP server

Create MCP Server:

pip install fluidmcp
fmcp install "Google Maps MCP Server/google-maps@0.6.2"

Output:

:wrench: Installing Google Maps MCP Server/google-maps@0.6.2
:cloud: Installing package from Fluid MCP registry...
:cloud: Downloading packages
:package: Saving metadata.json...
:information_source: Reading metadata.json for API key configuration
:key: Saving API key(s) to metadata.json
:information_source: API key(s) saved to metadata.json.
:white_check_mark: Installation completed successfully.

fmcp list

Output:

Installation directory: /content/.fmcp-packages
Google Maps MCP Server/google-maps@0.6.2

fmcp run all

Output:

✅ Wrote merged metadata to /content/.fmcp-packages/metadata_all.json
:blue_book: Reading metadata.json from /content/.fmcp-packages/Google Maps MCP Server/google-maps/0.6.2/metadata.json
google-maps {'command': 'npx', 'args': ['-y', '@modelcontextprotocol/server-google-maps'], 'env': {'GOOGLE_MAPS_API_KEY': '<YOUR_API_KEY>'}}
✅ Added google-maps endpoints
2025-06-06 09:19:04.284 | INFO     | fluidai_mcp.cli:run_all:279 - Starting FastAPI client server on port 8099
INFO:     Started server process [6848]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://0.0.0.0:8099 (Press CTRL+C to quit)

Quick-trying out MCP server:

# IMP NOTE: You have to add GOOGLE_MAPS_API_KEY in .fmcp-packages/{Package}/metadata.json
import requests
import json

mcp_url = "http://localhost:8099/google-maps/mcp"
mcp_payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "maps_search_places",
      "arguments": {
        "query": "coffee shops in San Francisco"
      }
    }
}
mcp_response = requests.post(mcp_url, json=mcp_payload)
print("Status code:", mcp_response.status_code)
# Print the response in pretty JSON format
try:
    parsed_response = json.loads(mcp_response.text)
    for item in parsed_response["result"]["content"]:
            if item["type"] == "text":
                nested_json = json.loads(item["text"])
                print(json.dumps(nested_json, indent=2))
    # print(json.dumps(mcp_response.json(), indent=2))
except Exception as e:
    print("Error decoding JSON:", e)

Output:

Status code: 200
{
  "places": [
    {
      "name": "The Coffee Movement",
      "formatted_address": "1030 Washington St, San Francisco, CA 94108, United States",
      "location": {
        "lat": 37.7947575,
        "lng": -122.4102936
      },
      "place_id": "ChIJoTMb3PKAhYARsXkQt469sBw",
      "rating": 4.8,
      "types": [
        "cafe",
        "food",
        "point_of_interest",
        "store",
        "establishment"
      ]
    },
    {
      "name": "Sextant Coffee Roasters",
      "formatted_address": "1415 Folsom St, San Francisco, CA 94103, United States",
      "location": {
        "lat": 37.7724716,
        "lng": -122.4040877
      },
      "place_id": "ChIJW9Zu0uGAhYARQ5p0JqvV0Ew",
      "rating": 4.6,
      "types": [
        "cafe",
        "restaurant",
        "food",
        "point_of_interest",
        "store",
        "establishment"
      ]
    }
  ]
}

You can further checkout 'examples/chat_google_maps.ipynb'

Using Server-Sent Events (SSE) for Streaming Responses

For MCP tools that support incremental or chunked data delivery, FluidMCP provides a Server-Sent Events (SSE) endpoint. This is particularly useful for long-running operations or when you want to process data as it arrives, rather than waiting for the entire response. To use this, you would typically make a POST request to the /{package_name}/sse endpoint with your standard JSON-RPC payload. The server will then hold the connection open and stream back events, where each event's data field will contain a part of the JSON response. Clients should be configured to listen for these events and process them accordingly. This allows for a more responsive user experience, especially when dealing with large language models or other tools that generate output progressively.

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Advanced Usage

Master Mode

Master mode allows centralized management of MCP servers using S3 storage:

# Install package for master mode (skips env prompts)
fluidmcp install package --master

# Run all servers using S3 configuration
fluidmcp run all --master

In master mode:

• Environment variables are managed via a central .env file
• Server metadata is stored in S3 (s3_metadata_all.json)
• Automatic synchronization across multiple environments

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Secure Mode

Enable secure mode for production deployments:

# Run with auto-generated token
fluidmcp run package --secure

# Run with custom token
fluidmcp run package --secure --token your-custom-token

Secure mode features:

• Bearer token authentication
• Encrypted communication between servers
• Environment variable injection for security tokens

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Port Management

FluidMCP automatically manages ports to avoid conflicts:

• Scans for available ports in range 8100-9000
• Kills existing processes when using --force-reload
• Assigns unique ports to each server in multi-server setups

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API Registry

FluidMCP CLI connects to the FluidMCP registry to download packages. The registry provides:

• Package versioning and metadata
• Secure package distribution via S3 pre-signed URLs
• Authentication and authorization
• Package discovery and search

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