广告合作
MCP.so
登录

AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveS…

@chin3

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

chin3

关于 AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch MCP Server

This project is a proof of concept for running a local-first multi-agent system using: 🤖 Local LLMs via Ollama 🧩 Simple function/tool-call detection using <tool_call>... 🔍 Brave Search API or optional Brave MCP plugin server 🧠 Two collaborating agents: Searcher and Synthesize

#multi-agent#ollama#brave-search

AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "Multi-Agent-Research-POC": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

AutoGen-Compatible Multi-Agent Research POC with Ollama + BraveSearch MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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 🧠 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

常见问题

1

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.

2

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.

3

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.

4

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.

5

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.

评论

AI 与智能体 分类下的更多 MCP 服务器

Pocket Network Agentic Marketplace: Pay-per-Call APIs

Pocket Network Foundation

MCP server for the Pocket Network agentic marketplace: search our catalog of data services and utilities and call them, paying per request in USDC on Base with x402. No account or API key. Search and describe are free; p

TruVerifAI Panel-review

TruVerifAI

TruVerifAI's Panel Review is the guardian agent for AI's highest-stakes coding decisions: four frontier models argue over an AI coding agent's riskiest designs, diffs, and commits before they execute, with local review g

1

Krafters

Krafters (Romain Duclos)

Krafters is a French club of specialized AIs for freelancers and small businesses. Its connector opens the member's AI kits for Facebook and Instagram ads, SEO/GEO and short videos directly in Claude, and gives the next

treg.to

Jason Zhou

OpenRouter for tools & data — 3,028 APIs for your agent, one token, pay per call. treg.to is a remote MCP server at https://treg.to/mcp/ that gives an agent 3,028 ready-to-call API endpoints across 82 platforms: SEO and

strac-mcp-dlp

strac-io

Detect and redact PII, PHI, PCI and secrets — SSNs, credit cards, passports, API keys and cloud credentials — in text and in local files, using the Strac DLP API. Five tools: redact_text, detect_sensitive_data, detect_fi

3
广告合作