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Fiware-MCP-server
Un primer servidor de protocolo de contexto de modelo fiware
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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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Reviews

user_iboEoYPT
I have been using Unity AI MCP Server by GrandMasterK414, and it's simply phenomenal. The seamless integration with various AI models and its intuitive interface makes managing AI projects a breeze. The performance is top-notch, and the support from the development team is commendable. Highly recommend this for anyone involved in serious AI development projects! Check it out at https://mcp.so/server/unity-ai-mcp-server/GrandMasterK414.