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Open Web Agent Rs MCP Server

@seemueller-io

Repository

Basic information

Category

AI & Agents

License

MIT license

Transports

stdio

Author

seemueller-io

About Open Web Agent Rs MCP Server

an mcp server with candle inference

#agent#rust#axum#llm#genaiscript

Open Web Agent Rs MCP Server config

Add this server to your MCP-compatible client using the configuration below.

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

Open Web Agent Rs MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

1

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

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

2

What are the runtime requirements?

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

3

Where does data live?

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

4

Are there any known limitations?

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

5

What transport or authentication does it use?

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

Comments

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