muse-glimmer-agent
Muse Glimmer + MCP + LangGraph (로컬)
다음을 수행하는 최소한의 Pydantic AI 에이전트입니다:
muse-glimmer(Meta의 30B agentic 모델)를 로컬 Ollama 인스턴스에서 실행합니다.MCP 지원: 로컬 FastMCP 서버(
mcp_server.py)가 stdio subprocess로 연결되어get_weather,get_current_time,list_ollama_models를 에이전트 도구로 노출합니다.전체 추적(traces, model requests, tool calls, output)을 로컬 Langfuse 인스턴스로 보내 관측 가능성을 확보합니다.
사전 요구 사항
Ollama가 실행 중이고
muse-lim-mer모델이 pull되어 있는 상태:ollama pull muse-glimmerhttp://localhost:3000에서 접근 가능한 로컬 Langfuse 인스턴스 (예: Langfuse 저장소의docker compose사용).uv 사용 (또는
python3 -m venv+pip).
Related MCP server: MCP Ollama Consult Server
설정
cp .env.example .env # then fill in your Langfuse keys
uv sync # installs pydantic-ai, fastmcp, langfuse, ....env:
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
LANGFUSE_BASE_URL=http://localhost:3000
LANGFUSE_HOST=http://localhost:3000
OLLAMA_BASE_URL=http://localhost:11434/v1
OLLAMA_MODEL=muse-glimmer실행
uv run python agent.py에이전트는 세 가지 데모 프롬프트에 응답하며, 필요할 때 MCP 도구를 호출합니다:
🧑 User: What is the weather in Paris today?
🤖 Agent: Weather in Paris: clear skies, 22°C, humidity 51%.
🧑 User: What time is it in Tokyo right now?
🤖 Agent: The current time in Asia/Tokyo is 2026-08-25 21:04:33 JST.
🧑 User: Which Ollama models are available locally?
🤖 Agent: NAME ID SIZE MODIFIED ...관측 가능성 (Langfuse)
http://localhost:3000 → Traces를 열어. 각 실측은 muse-glimmer-mcp-agent라는 정의 trace를 만듭며, 모델 요청(입력/출력 토근), 각 MCP 도구 호출 span, 그리고 입출, 출출, 지연, side 비용을 확ㅂ할 수 있습니다.
에이전트를 MCP 서버로 노출
agent_mcp_server.py는 아키텍처를 뒤바니다. 에이전트 자가 자체가 MCP 서버가 되어 ask_agent(prompt) 하나의 CLI를 노출하며, Clode Desktop, VS Code, Cursor, 또는 에이전트나 MCP 클라이언트 모두가 사용할 수 있습니다. 각 호출은 muse-밎l` via Ollama, it still uses internal MCP tool for 실행하고, measured and measured to Langfuse at the end.
서버 실행
uv run python agent_mcp_server.py클라이언트 구성
uv으로 관리되는 venv의 Python (uv run --project <repo> python도 됩니다)을 사용하여 모든 MCP 클라이언트를 이 서버에 연결하세요. 예:
Claude Desktop —:
{
"mcpServers": {
"muse-glimmer-agent": {
"command": "/home/d3lee/.local/bin/uv",
"args": ["run", "--project", "/home/d3lee/my-repos/pydantic-ai-mcp-server-sample", "python", "agent_mcp_server.py"]
}
}
}Var아 기타 (예: .vscode/mcp.json):
{
"servers": {
"muse-glimmer-agent": {
"type": "stdio",
"command": "uv",
"args": ["run", "--project", "/home/d3lee/my-repos/pydantic-ai-mcp-server-sample", "python", "agent_mcp_server.py"]
}
}
}[Cursor mcp] — .cursor/mcp.json:
{
"mcpServers": {
"muse-glimmer-agent": {
"command": "uv",
"args": ["run", "--project", "/home/d3lee/my-repos/pydantic-ai-mcp-server-sample", "python", "agent_mcp_server.py"]
}
}
}Layout
파일 | 설명 |
| Pydantic AI agent: Ollama model + MCP mod + LangGraph |
| FastMCP server (stdio) exposes local tools |
| exports the agent as MCP server ( |
| LangGraph + Ollama configuration |
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