polypack-mcp

An MCP server that exposes Polypack as persistent adaptive memory. MCP-specific tools live here; the database remains an independent dependency.

Install and run

The simplest installation is from PyPI:

python3 -m pip install 'polypack-mcp[polypack]'

For one MCP client, use the default stdio server configuration. For Claude and Codex sharing the same durable memory, install once and create a long-running user service:

polypack-mcp setup --store ~/.local/share/polypack-mcp

This starts an SSE server at http://127.0.0.1:8765/sse, restarts it after a failure, and prints client configuration snippets. The setup command uses systemd --user; on systems without systemd, start the server directly:

polypack-mcp --transport sse --port 8765 --store ~/.local/share/polypack-mcp

In shared SSE mode, configure both clients with the URL. Do not configure them with a command and --store, since that starts two processes competing for the same durable store.

Codex (~/.codex/config.toml):

[mcp_servers.polypack]
  url = "http://127.0.0.1:8765/sse"

Claude Desktop:

{
  "mcpServers": {
    "polypack": { "url": "http://127.0.0.1:8765/sse" }
  }
}

Debian package

The Debian package installs and starts a system-level polypack-mcp service automatically. It runs as the dedicated polypack user, stores data in /var/lib/polypack-mcp, and exposes the same local SSE endpoint:

sudo apt install ./polypack-mcp_<version>_amd64.deb

After installation, point Claude and Codex at http://127.0.0.1:8765/sse. The default port can be changed in /etc/default/polypack-mcp, followed by a service restart. The service can be managed with:

sudo systemctl status polypack-mcp
sudo systemctl restart polypack-mcp

The PyPI installation remains user-managed and uses polypack-mcp setup to create a per-user service instead.

Run manually

pip install -e '.[polypack]'
polypack-mcp --store ./polypack-data

The server exposes eight focused tools: memory_store, memory_recall, memory_context, memory_feedback, memory_suppress, memory_supersede, memory_consolidate, and graph_query. It also publishes context, active-memory, schema, and stats resources under polypack://.

Retrieval tools return {items, metadata}. Metadata includes candidate and excluded counts, context matches, score components, fallback behavior, the retrieval version, and selection statistics. memory_context uses estimated tokens (ceil(content characters / 4), minimum one) as its token_budget. An item is never returned if it would exceed the remaining budget; budgets less than or equal to zero are rejected. Context is a soft preference: matching memories are preferred and unscoped global memories may be used as fallback. Pass strict_context: true for isolation. An empty isolated result reports reason: "no_context_match" and the searched context.

Feedback is activation feedback: useful=true reinforces a memory and useful=false provides negative retrieval feedback. Responses expose activation before and after plus whether learned weights changed. Supersession and consolidation materialize SUPERSEDES, SUPERSEDED_BY, and CONSOLIDATED_FROM graph edges.

Pass --store to open a durable Polypack directory. Without it, the server uses the in-memory reference backend, which is convenient for smoke tests. The polypack extra requires polypack-db>=3.2.0 and uses its native ActivationEngine.working_memory selector for context assembly.

Development

pip install -e '.[dev]'
pytest

The test suite includes an MCP client/server protocol smoke test covering tool discovery, memory storage, recall, and resource reads.