Mcps
This project provides multiple Model Context Protocol servers, including web search, weather query, and memory storage functions, enabling AI models to integrate external tools and data sources.
rating : 2.5 points
downloads : 5.6K
What is an MCP server?
An MCP server is a tool server based on the Model Context Protocol standard, enabling AI models to access external data sources and tools. It's like giving AI models 'hands and eyes', allowing them to search the web, obtain weather information, store memories, etc.How to use these servers?
Run the servers through Docker containers, and then configure the connection in AI applications (such as LocalAI). The servers communicate with AI models through a standard protocol, providing real - time tool invocation capabilities.Applicable scenarios
Suitable for various scenarios that require enhancing the capabilities of AI models: information retrieval, personalized memory, real - time data acquisition, etc. It is particularly suitable for chatbots, intelligent assistants, and knowledge Q&A systems.Main Features
Web Search
Use the DuckDuckGo search engine to search for web information in real - time, supporting a configurable number of search results
Weather Query
Get the current weather and multi - day weather forecasts for global cities, including temperature, wind speed, and weather descriptions
Persistent Memory
Store and retrieve information across sessions, support adding, searching, and deleting memory entries, with timestamp tracking
Containerized Deployment
All servers provide Docker images, supporting rapid deployment and multi - architecture operation
Data Validation
Strict JSON Schema validation ensures the integrity and correctness of input and output data
Advantages
Ready to use: Pre - configured Docker images for rapid deployment
Standardized: Follows the MCP protocol and is compatible with various AI clients
Lightweight: Each server has a focused function and consumes few resources
Scalable: Easy to add new tools and functions
Persistent: The memory server supports cross - session data storage
Limitations
Network dependency: Search and weather services require an Internet connection
Function limitation: Each server has a relatively single function
Configuration requirements: Basic Docker and configuration knowledge is required
Data privacy: Memory server data is stored in local files
How to Use
Select the required server
Choose the appropriate server according to your needs: search, weather, or memory function
Run the Docker container
Use the provided Docker command to start the server container
Configure the AI client
Configure the server connection in LocalAI or other MCP clients
Start using
The AI model can now call the tools provided by the server through natural language
Usage Examples
Real - time information retrieval
When an AI model needs the latest information, it automatically calls the search server to obtain real - time data
Travel planning assistant
Provide weather information for the destination when helping users plan a trip
Personalized service
Remember user preferences and provide a personalized experience
Knowledge update
When the information in the AI knowledge base is outdated, search for the latest information to supplement it
Frequently Asked Questions
Do MCP servers require payment?
Do these servers support Chinese?
How to ensure data privacy?
Can multiple servers be run simultaneously?
What is the performance of the servers?
How to add a custom server?
Related Resources
Project code repository
Complete source code and development documentation
Model Context Protocol official website
Official documentation and specifications of the MCP protocol
LocalAI documentation
How to configure and use MCP servers in LocalAI
Docker image repository
Download Docker images for all servers
MCP SDK documentation
Go language MCP development toolkit

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