MCP ExplorerExplorer

Multi Agent Research Poc

@chin3on 17 days ago
1ย MIT
FreeCommunity
AI Systems
This project is a proof of concept for running a local-first multi-agent system using: ๐Ÿค– Local LLMs via Ollama ๐Ÿงฉ Simple function/tool-call detection using <tool_call>... ๐Ÿ” Brave Search API or optional Brave MCP plugin server ๐Ÿง  Two collaborating agents: Searcher and Synthesizer

Overview

What is Multi Agent Research Poc

Multi-Agent-Research-POC is a proof of concept for a local-first multi-agent system that utilizes local LLMs via Ollama, tool-call detection, and web search capabilities through the Brave Search API or Brave MCP plugin server. It features two collaborating agents: Searcher and Synthesizer.

Use cases

Use cases include academic research where the Searcher agent retrieves relevant information and the Synthesizer agent summarizes findings, as well as automated customer support systems that require information gathering and response generation.

How to use

To use Multi-Agent-Research-POC, clone the repository, install the required dependencies, set up your Brave API key in the .env file, run Ollama locally, and execute the main program. You can switch between using the Brave Search API and the Brave MCP plugin server.

Key features

Key features include local LLMs via Ollama, tool-call detection using a specific syntax, web search integration through Brave Search API or MCP plugin, and two collaborative agents for searching and synthesizing information.

Where to use

Multi-Agent-Research-POC can be used in various fields such as research, data analysis, and any application requiring collaborative information retrieval and synthesis using AI agents.

Content

๐Ÿง  AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch

This project is a proof of concept for a local-first multi-agent system using:

  • ๐Ÿค– Local LLMs via Ollama
  • ๐Ÿงฉ Tool-call detection using <tool_call>... syntax
  • ๐Ÿ” Web search via Brave Search API or Brave MCP plugin server
  • ๐Ÿง  Two collaborating agents: Searcher and Synthesizer

๐Ÿ“ Folder Structure

MultiResearchPOC/
โ”œโ”€โ”€ main.py                   # Entry point
โ”œโ”€โ”€ agents/
โ”‚   โ”œโ”€โ”€ searcher.py           # Ollama-powered research agent
โ”‚   โ””โ”€โ”€ synthesizer.py        # Summarizer agent
โ”œโ”€โ”€ tools/
โ”‚   โ”œโ”€โ”€ tool_parser.py        # Tool call detection logic
โ”‚   โ””โ”€โ”€ tool_registry.py      # Tool dispatcher (API or MCP)
โ”œโ”€โ”€ .env                      # Contains BRAVE_API_KEY
โ””โ”€โ”€ requirements.txt          # Python dependencies

๐Ÿš€ Getting Started

1. Clone the project

git clone <your-repo-url>
cd MultiResearchPOC

2. Install dependencies

pip install -r requirements.txt

3. Set up your .env

echo "BRAVE_API_KEY=your_brave_api_key_here" > .env

Get your Brave API key at: https://developer.brave.com/api-search/

4. Run Ollama locally

ollama run llama3:8b

If using Docker: make sure to reference the host as http://host.docker.internal:11434

5. Run the program

python main.py

You should see:

  • A response from the Searcher agent
  • A tool call triggered
  • Search results pulled from Brave
  • A final summary from the Synthesizer agent

๐Ÿ” Switching Between API and MCP Plugin

Option 1: Brave Search API (default)

Used by default via:

"BraveSearch": call_brave_api

Option 2: Brave MCP Plugin Server

  1. Start the plugin server:
npx @modelcontextprotocol/server-brave-search
  1. Update tools/tool_registry.py:
# "BraveSearch": call_brave_api,
"BraveSearch": call_brave_mcp_server

๐Ÿ”ฎ Next Steps & Improvements

Feature Description
๐Ÿง  Add Planner Agent Dynamically decide which agent/tool to call
๐Ÿงฉ Add More Tools CrunchbaseSearch, TwitterTrends, YouTubeSearch, etc.
๐Ÿ“„ Markdown Output Save session logs for review or integration with Obsidian
๐Ÿ–ผ๏ธ Add UI Use Chainlit, FastAPI, or Discord bot for interaction
๐ŸŒ Wrap as API Convert to a local API for web or CLI usage

๐Ÿ“œ Sample Output

๐Ÿค– Searcher Response:
<tool_call>BraveSearch({"query": "African AI startups 2024 promising not mainstream"})</tool_call>

๐ŸŒ Tool Output:
โ€ข AI 100: ...
โ€ข Five African AI startups to watch in 2023 ...

๐Ÿง  Final Summary:
- CB Insights lists top private AI companies...
- 5 African startups solving problems in healthcare, marketing...

๐Ÿ™Œ Credits


For questions or ideas, open an issue or start a discussion!

๐Ÿ—๏ธ Built for the Microsoft AI Agents Hackathon
This project was created as part of the Microsoft AI Agents Hackathon โ€” a challenge focused on building intelligent, tool-using, autonomous agents powered by open-source and Microsoft technologies.

The goal of this project is to showcase a local-first, multi-agent system that can:

Generate dynamic tool calls

Perform live web research using Brave Search

Collaborate between agents to synthesize useful insights

๐Ÿ”— Submission: [TBD]

local multi-agent AI research bot | Ollama + Brave + AutoGen | Built for Microsoft AI Agents Hackathon

Disclaimer

This project is a personal proof-of-concept developed entirely outside of my employment, using personal time and tools. It is unrelated to any current or anticipated business activities of my employer and contains no proprietary or confidential information.

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