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Gomcptest
This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.
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A context management and caching MCP server based on Gemini, supporting a large context window of 2M tokens and providing session management and API caching functions.
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Gemini Cli MCP
An MCP server integrated with the Gemini CLI tool, providing chat, content generation, and model list functions.
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MCP Gemini Grounding
An MCP server based on the Gemini API, providing AI - driven web search and summarization services, capable of synthesizing information and returning comprehensive answers with references.
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Gemini Bridge
Gemini Bridge is a lightweight MCP server that connects AI programming assistants to Google Gemini AI through the official CLI, supporting multi - client interaction without API costs.
Python
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Gemini MCP Server
A Gemini model - integrated MCP server based on FastMCP, implemented in Python and deployed via Docker
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Advanced Reasoning With DeepSeek
An advanced reasoning and reflection tool based on the Gemini API
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Gemini MCP Server
An MCP server implementation based on TypeScript that integrates the Gemini model by directly calling the Google Gemini API, supports the latest Gemini 2.0 Flash model, and maintains conversation context.
TypeScript
4.6K
2.5 points
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