Open Web Agent Rs MCP Server

@seemueller-io

Repository

Basic information

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

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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