What are the runtime requirements?
Python 3.8+, Chroma 0.4.0+, and MCP SDK 0.1.0+.
@privetin
基本信息
A Model Context Protocol (MCP) server implementation that provides vector database capabilities through Chroma.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"chroma": {
"command": "uv",
"args": [
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
An MCP server that provides vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage. It is designed for developers integrating semantic search into AI applications.
Install dependencies with uv venv and uv sync --dev --all-extras, then start the server with uv run chroma. Add the configuration to your Claude Desktop config file to enable the server, then interact via MCP tools like create_document and search_similar.
Python 3.8+, Chroma 0.4.0+, and MCP SDK 0.1.0+.
Data is stored in `src/chroma/data` directory and persists between server restarts.
It provides CRUD tools for documents (`create_document`, `read_document`, `update_document`, `delete_document`, `list_documents`) and a `search_similar` tool for semantic search with optional filters.
Add a `chroma` entry to your `claude_desktop_config.json` using `uv` with `--directory` pointing to the server’s path and `run chroma` as args.
Common errors include “Document already exists [id=X]”, “Document not found [id=X]”, “Invalid input: Missing document_id or content”, and “Invalid filter”.

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