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Copilot Memory MCP

Official registry Data and databases

Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

OCI package ghcr.io/labforgedev/copilot-memory-mcp:1.0.0
Claude Code 
claude mcp add copilot-memory-mcp -- docker run -i --rm ghcr.io/labforgedev/copilot-memory-mcp:1.0.0
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "copilot-memory-mcp": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "ghcr.io/labforgedev/copilot-memory-mcp:1.0.0"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. copilot-memory-mcp
  2. Why this exists
  3. Quick start
  4. MCP tools
  5. Copilot instructions & agents (examples)
  6. Architecture
  7. Project layout
  8. Development
  9. Environment variables
  10. License

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.

Quick start

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.

MCP tools

ToolDescription
create_memoryStore a new memory with title, content, optional project scope and tags
search_memoriesSemantic vector search; filter by project and/or tags
update_memoryUpdate an existing memory by ID; re-embeds on change
delete_memoryPermanently delete a memory by ID
list_memoriesBrowse 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.

FileConsumed by
AGENTS.mdOpenAI Codex, Claude Code, and most agent runtimes
CLAUDE.mdClaude Code (claude CLI)
.cursorrulesCursor (legacy format, project-root)
.cursor/rules/memory-tools.mdcCursor (modern per-rule format)
.github/copilot-instructions.mdGitHub Copilot in VS Code
.github/prompts/save-memory.prompt.mdVS Code /save-memory prompt
.github/prompts/recall-memory.prompt.mdVS Code /recall-memory prompt
.github/agents/memory.mdVS Code @memory custom agent mode

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.toml

Development

Install dependencies
pip install -e ".[dev]"
Run tests
pytest

Tests 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.py

Environment variables

VariableDefaultDescription
SENTENCE_TRANSFORMERS_HOME/app/modelsModel cache directory
CHROMA_PATH/data/chromaChromaDB persistence path
PORT8000HTTP server port

Copy .env.example to .env and adjust if needed.

License

MIT — see LICENSE.

Frequently asked questions

What is Copilot Memory MCP?

Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.

How do I install Copilot Memory MCP?

It runs on your machine. In Claude Code: claude mcp add copilot-memory-mcp -- docker run -i --rm ghcr.io/labforgedev/copilot-memory-mcp:1.0.0. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Copilot Memory MCP need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Copilot Memory MCP open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Copilot Memory MCP?

It is published by LabForgeDev. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.