🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch

What is 🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch?

A proof-of-concept for a local-first multi-agent system using Ollama (local LLMs) and Brave Search. It features two collaborating agents—Searcher and Synthesizer—that detect tool calls via <tool_call> syntax and can optionally integrate with the Brave MCP plugin server. Built for developers exploring autonomous, tool-using agents.

How to use 🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch?

Clone the repo, install Python dependencies (pip install -r requirements.txt), set a BRAVE_API_KEY in .env, run Ollama locally (ollama run llama3:8b), then execute python main.py. To switch from the default Brave Search API to the Brave MCP plugin, start the plugin server (npx @modelcontextprotocol/server-brave-search) and update tools/tool_registry.py.

Key features of 🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch

• Local-first multi-agent system with Searcher and Synthesizer agents
• Web search via Brave Search API or Brave MCP plugin server
• Tool-call detection using <tool_call> syntax
• Supports switching between API and MCP backends
• Designed for the Microsoft AI Agents Hackathon

Use cases of 🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch

• Conduct web research entirely with local AI agents
• Synthesize multiple search results into a coherent summary
• Prototype autonomous, tool-using agents without cloud dependencies
• Test multi-agent collaboration patterns with local LLMs

FAQ from 🧠 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch

What does this project do?

It runs two agents (Searcher and Synthesizer) locally with Ollama, queries the web via Brave Search (API or MCP plugin), and produces a final summary from search results.

What runtime dependencies are required?

Ollama (with a model like llama3:8b), Python 3, and a Brave Search API key. Optionally, Node.js/npx for the MCP plugin.

How do I switch between the Brave API and the MCP plugin?

By default the tool uses call_brave_api. To use the MCP plugin, start the plugin server (npx @modelcontextprotocol/server-brave-search) and change tools/tool_registry.py to use call_brave_mcp_server instead.

Where does data from searches live?

Search results are fetched from Brave and processed entirely locally; no data is stored externally. The project saves no session logs by default.

Is this project ready for production?

No—it is a proof of concept built for the Microsoft AI Agents Hackathon. The README lists planned improvements like a Planner agent, more tools, a UI, and API wrapping.