copilot-memory-mcp
Provides persistent, project-scoped memory for GitHub Copilot in VS Code, enabling semantic search and retrieval of memories across sessions.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@copilot-memory-mcpSearch my memories for the database schema decision."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
copilot-memory-mcp
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.
Why this exists
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.
Related MCP server: AIVectorMemory
Quick start
docker compose up -dThe 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.
MCP tools
Tool | Description |
| Store a new memory with title, content, optional project scope and tags |
| Semantic vector search; filter by project and/or tags |
| Update an existing memory by ID; re-embeds on change |
| Permanently delete a memory by ID |
| Browse memories with pagination (lightweight, no content) |
Copilot instructions & agents (examples)
Ready-to-use examples are in examples/. Copy the relevant file(s) into the root or .github/ of your own project.
File | Consumed by |
OpenAI Codex, Claude Code, and most agent runtimes | |
Claude Code ( | |
Cursor (legacy format, project-root) | |
Cursor (modern per-rule format) | |
GitHub Copilot in VS Code | |
VS Code | |
VS Code | |
VS Code |
Architecture
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)Project layout
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.tomlDevelopment
Install dependencies
pip install -e ".[dev]"Run tests
pytestTests use an ephemeral in-memory ChromaDB and a mocked embedding function — no Docker, no model download required.
Run the server locally (no Docker)
pip install -e .
PYTHONPATH=. python app/main.pyEnvironment variables
Variable | Default | Description |
|
| Model cache directory |
|
| ChromaDB persistence path |
|
| HTTP server port |
Copy .env.example to .env and adjust if needed.
License
MIT — see LICENSE.
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