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open-web-agent-rs

@seemueller-io

代码仓库

关于 open-web-agent-rs

an mcp server with candle inference

#agent#rust#axum#llm#genaiscript

基本信息

分类

AI 与智能体

许可证

MIT license

运行时

rust

传输方式

stdio

发布者

seemueller-io

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "open-web-agent-rs": {
      "command": "docker",
      "args": [
        "compose",
        "up",
        "-d",
        "searxng"
      ]
    }
  }
}

工具

未检测到工具

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。

概览

What is open-web-agent-rs?

open-web-agent-rs is a Rust-based web agent that includes an embedded OpenAI‑compatible inference server. It supports only Gemma models and is designed for developers who want a lightweight, local web agent with custom inference.

How to use open-web-agent-rs?

Copy the .env.example to .env, install dependencies with bun i, start the local inference server by running cargo run --release -- --server inside local_inference_server, launch the SearXNG search engine with docker compose up -d searxng, then run bun dev to start the agent.

Key features of open-web-agent-rs

  • Rust‑based implementation for performance and reliability
  • Embedded OpenAI‑compatible inference server
  • Supports Gemma models only
  • Integrates with SearXNG for web search
  • Quick setup with Bun, Cargo, and Docker

Use cases of open-web-agent-rs

  • Creating a private web agent with local Gemma model inference
  • Experimenting with Rust‑based agent workflows
  • Building a self‑hosted, search‑enabled assistant

FAQ from open-web-agent-rs

Which models does open-web-agent-rs support?

It supports only Gemma models. Other model families are not compatible.

What are the runtime requirements?

You need Rust, Bun, and Docker installed. The local inference server is written in Rust and runs via Cargo.

Where does data live?

Data can be configured in the .env file. The SearXNG instance runs locally via Docker.

Are there any known limitations?

The inference server is embedded and supports only Gemma models, so flexibility is limited to that model family.

What transport or authentication does it use?

The README does not specify authentication or transport details. It uses an OpenAI‑compatible API interface locally.

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