CoinGecko MCP Server

# Unichat MCP Server in TypeScript Also available in [Python](https://github.com/amidabuddha/unichat-mcp-server) -- <h4 align="center"> <a href="https://glama.ai/mcp/servers/ub2u8wtbbv"><img width="380" height="200" src="https://glama.ai/mcp/servers/ub2u8wtbbv/badge" alt="unichat-ts-mcp-server MCP server" /></a> <a href="https://smithery.ai/server/unichat-ts-mcp-server"><br> <img src="https://smithery.ai/badge/unichat-ts-mcp-server" alt="Smithery Server Installations" /> </a> </h4> Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI or DeepSeek using MCP protocol via tool or predefined prompts. Vendor API key required. Both STDIO and SSE transport mechanisms supported via arguments. ### Tools The server implements one tool: - `unichat`: Send a request to unichat - Takes "messages" as required string arguments - Returns a response ### Prompts - `code_review` - Review code for best practices, potential issues, and improvements - Arguments: - `code` (string, required): The code to review" - `document_code` - Generate documentation for code including docstrings and comments - Arguments: - `code` (string, required): The code to comment" - `explain_code` - Explain how a piece of code works in detail - Arguments: - `code` (string, required): The code to explain" - `code_rework` - Apply requested changes to the provided code - Arguments: - `changes` (string, optional): The changes to apply" - `code` (string, required): The code to rework" ## Development Install dependencies: ```bash npm install ``` Build the server: ```bash npm run build ``` For development with auto-rebuild: ```bash npm run watch ``` ## Installation ### Installing via Smithery To install Unichat MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/unichat-ts-mcp-server): ```bash npx -y @smithery/cli install unichat-ts-mcp-server --client claude ``` ### Installing manually To use with Claude Desktop, add the server config: On MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json` On Windows: `%APPDATA%/Claude/claude_desktop_config.json` Run locally: ```json { "mcpServers": { "unichat-ts-mcp-server": { "command": "node", "args": [ "{{/path/to}}/unichat-ts-mcp-server/build/index.js" ], "env": { "UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME", "UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY" } } } ``` Run published: ```json { "mcpServers": { "unichat-ts-mcp-server": { "command": "npx", "args": [ "-y", "unichat-ts-mcp-server" ], "env": { "UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME", "UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY" } } } ``` > Runs in STDIO by default or with argument `--stdio`. To run in SSE add argument `--sse` ```bash npx -y unichat-ts-mcp-server --sse ``` **Supported Models:** > A list of currently supported models to be used as `"YOUR_PREFERRED_MODEL_NAME"` may be found [here](https://github.com/amidabuddha/unichat-ts/blob/main/src/models.ts). Please make sure to add the relevant vendor API key as `"YOUR_VENDOR_API_KEY"` **Example:** ```json "env": { "UNICHAT_MODEL": "gpt-4o-mini", "UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY" } ``` ### Debugging Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script: ```bash npm run inspector ``` The Inspector will provide a URL to access debugging tools in your browser. If you experience timeouts during testing in SSE mode change the request URL on the inspector interface to: http://localhost:3001/sse?timeout=600000