A First FIWARE Model Context Protocol Server
What is dncampo FIWARE MCP Server
FIWARE MCP Server
This is a first implementation of a FIWARE Model Context Protocol (MCP) Server that provides a bridge between the Context Broker and other services. The server implements basic operations for interacting with a FIWARE Context Broker.
Objectives
- Create a basic MCP server implementation for FIWARE
- Provide simple tools for Context Broker interaction
- Demonstrate basic intent CRUD operations with the Context Broker
- Serve as a foundation for more complex MCP implementations
Features
- Context Broker version checking
- Query capabilities for the Context Broker
- Entity publishing and updating
Prerequisites
- Python 3.7 or higher
- pip (Python package installer)
- Access to a FIWARE Context Broker instance
Installation
- Clone this repository:
git clone <repository-url>
cd FIWARE_MCP_01
- Install the required dependencies:
pip install -r requirements.txt
Claude Desktop integration
mcp install server.py
# Custom name
mcp install server.py --name "FIWARE MCP Server"
# Environment variables, if any
mcp install server.py -v API_KEY=abc123 -v DB_URL=postgres://...
mcp install server.py -f .env
Usage
Start the MCP server:
python server.py
# or
mcp run server.py
The server will start on 127.0.0.1:5001
by default.
Available Tools
-
CB_version
- Checks the version of the Context Broker
- Default parameters: address="localhost", port=1026
- Returns: JSON string with version information
-
query_CB
- Queries the Context Broker
- Parameters:
- address (default: "localhost")
- port (default: 1026)
- query (default: "")
- Returns: JSON string with query results
-
publish_to_CB
- Publishes or updates entities in the Context Broker
- Parameters:
- address (default: "localhost")
- port (default: 1026)
- entity_data (required: dictionary with entity information)
- Returns: JSON string with operation status
Example Usage
# Example entity data
entity_data = {
"id": "urn:ngsi-ld:TemperatureSensor:001",
"type": "TemperatureSensor",
"temperature": {
"type": "Property",
"value": 25.5
},
"@context": "https://uri.etsi.org/ngsi-ld/v1/ngsi-ld-core-context.jsonld"
}
# Publish to Context Broker
result = publish_to_CB(entity_data=entity_data)
Configuration
The server can be configured by modifying the following parameters in server.py
:
- Host address
- Port number
- Timeout settings
Error Handling
The server includes comprehensive error handling for:
- Network connectivity issues
- Invalid responses from the Context Broker
- Malformed entity data
- Server shutdown
Contributing
Feel free to submit issues and enhancement requests!
License
This project is licensed under the Apache License 2.0.
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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