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💡 Description
This project implements an MCP server that allows access to the documentation of various technologies through the Gemini API, with a huge context window of 2 million tokens. It streamlines the process of querying documentation, overcoming traditional search engine limitations and ensuring contextually relevant answers.
📝 JSON Entries
{
"mcpServers": [
{
"Gemini Docs MCP Server": {
"env": {
"GEMINI_API_KEY": "<your_gemini_api_key>"
},
"args": [
"--watch",
"path/to/repo/cosa-sai-mcp/src/index.ts",
"--verbose"
],
"command": "bun"
}
}
]
}🛠️ Tools
BunSmithery
⚡ Features
- Access to a curated knowledge base
- Customized and well-reasoned responses
- No need for a custom retriever or vector database
💬 Example Queries
- Can X be done with this technology?
- What are the alternatives to do X?
- Is this snippet of code a good practice?