接入你的智能体
發布者自己的指令。不是 PlugMCP 端點。
用我們的金鑰與日誌託管一份副本。
docker run -i --rm ghcr.io/labforgedev/copilot-memory-mcp:1.0.0Claude Code 沒有本機指令的安裝連結。複製下方指令並在終端機中執行。
claude mcp add io.github.labforgedev-copilot-memory-mcp -- docker run -i --rm ghcr.io/labforgedev/copilot-memory-mcp:1.0.0在終端機中執行。
{ "mcpServers": { "io.github.labforgedev-copilot-memory-mcp": { "command": "docker", "args": [ "run", "-i", "--rm", "ghcr.io/labforgedev/copilot-memory-mcp:1.0.0" ] } }}claude_desktop_config.json
遠端 URL 還是本機指令？ 兩種安裝方式的差異
來自發布者
Persistent semantic memory for GitHub Copilot in VS Code.
A local MCP server that gives Copilot durable, project-scoped memory across sessions. Memories are stored in an embedded ChromaDB vector database with all-MiniLM-L6-v2 embeddings, enabling semantic retrieval (RAG). Everything runs in a single Docker container — no cloud services required.
Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
Copilot starts every session with a blank slate. This MCP server gives it a persistent, searchable knowledge base so decisions, conventions, and context carry over between sessions — all running locally in Docker.
docker compose up -d
The server starts on http://localhost:8000/sse.
The .vscode/mcp.json already points Copilot at the server — no further VS Code configuration needed.
A sample config is provided in examples/vscode/mcp.json. Copy it to your project's .vscode/mcp.json.
Ready-to-use examples are in examples/. Copy the relevant file(s) into the root or .github/ of your own project.
VS Code / Copilot
│ MCP HTTP/SSE (port 8000)
▼
┌─────────────────────────────────┐
│ Docker Container │
│ │
│ FastMCP Server (port 8000) │
│ └── 5 MCP tools │
│ │
│ sentence-transformers │
│ └── all-MiniLM-L6-v2 │
│ (384-dim embeddings) │
│ │
│ ChromaDB (embedded) │
│ └── collection "memories" │
└──────────┬──────────────────────┘
│ Docker named volume
▼
/data/chroma (persisted DB)
copilot-memory-mcp/
├── app/
│ ├── main.py # FastMCP server, tool registration
│ ├── memory_store.py # ChromaDB wrapper (CRUD + search)
│ ├── embeddings.py # sentence-transformers loader + encode()
│ └── tools/
│ ├── create_memory.py
│ ├── search_memories.py
│ ├── update_memory.py
│ ├── delete_memory.py
│ └── list_memories.py
├── tests/
│ ├── test_memory_store.py
│ └── test_tools.py
├── Dockerfile
├── docker-compose.yml
└── pyproject.toml
pip install -e ".[dev]"
pytest
Tests use an ephemeral in-memory ChromaDB and a mocked embedding function — no Docker, no model download required.
pip install -e .
PYTHONPATH=. python app/main.py
Copy .env.example to .env and adjust if needed.
MIT — see LICENSE.
Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
{ "mcpServers": { "io.github.labforgedev-copilot-memory-mcp": { "command": "docker", "args": [ "run", "-i", "--rm", "ghcr.io/labforgedev/copilot-memory-mcp:1.0.0" ] } }}工具
尚無工具清單。遠端伺服器會在首次健康檢查後取得工具清單。
常見問題
在本頁複製適用於 Cursor、Claude Desktop、Claude Code 或 VS Code 的 http 設定。它使用發布者的安裝方式，而不是 PlugMCP 代理伺服器。
這筆記錄未列出必要的環境變數。
Copilot Memory MCP 透過 HTTP 存取。
上次檢查時間：2026-11-09。 Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.