How do I install Polypack Memory?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Polypack Memory need an API key?

No required environment variable is listed on this record.

What transport does Polypack Memory use?

Polypack Memory runs locally over stdio.

When was Polypack Memory last checked?

Last checked 2026-11-09. MCP server exposing Polypack as persistent adaptive memory

Polypack Memory MCP server

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Add to Cursor Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Local command

uvx polypack-mcp==0.1.31

Claude Code has no install link for a local command. Copy the command below and run it in a terminal.

shClaude Code

1claude mcp add io.github.imattau-polypack-mcp -- uvx polypack-mcp==0.1.31

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.imattau-polypack-mcp": {4      "command": "uvx",5      "args": [6        "polypack-mcp==0.1.31"7      ]8    }9  }10}

claude_desktop_config.json

Local · pypiPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Version: 0.1.31
Last checked

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

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 a stateless Streamable HTTP server at http://127.0.0.1:8765/mcp/, 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 streamable-http --port 8765 --store ~/.local/share/polypack-mcp

In shared Streamable HTTP 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/mcp/"

Claude Desktop:

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

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 Streamable HTTP endpoint:

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

After installation, point Claude and Codex at http://127.0.0.1:8765/mcp/. 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.

Optional semantic retrieval

The default installation uses Polypack's local graph, activation, and lexical retrieval without downloading an AI model. To enable local Qwen semantic retrieval, run:

sudo polypack-mcp embeddings setup qwen3 --system --store /var/lib/polypack-mcp

This creates a managed localhost helper, downloads Qwen once into the store's embedding cache, and reindexes existing memories. The model is not bundled in the Debian/RPM package.

The helper loads Qwen3-Embedding-0.6B in bfloat16 (~1GB resident once loaded, versus ~2.4GB in fp32) and unloads it after 15 minutes of inactivity, reloading automatically on the next request. memory_recall results include a semantic entry in scoreComponents whenever the helper is reachable, alongside lexical and activation — the three sum to the reported score. If the helper is stopped or errors, recall falls back to lexical + activation scoring automatically. Check or disable it with:

polypack-mcp embeddings status
sudo polypack-mcp embeddings disable --system --store /var/lib/polypack-mcp

For a PyPI user service, omit sudo --system and use the user store:

polypack-mcp embeddings setup qwen3

APT repository

The latest Debian package is also published to the public APT repository at https://imattau.github.io/polypack-mcp. Configure it with the repository's signing key, then install and update normally:

curl -fsSL https://imattau.github.io/polypack-mcp/gpg.key \
  | sudo gpg --dearmor -o /usr/share/keyrings/polypack-mcp.gpg
echo "deb [signed-by=/usr/share/keyrings/polypack-mcp.gpg] https://imattau.github.io/polypack-mcp stable main" \
  | sudo tee /etc/apt/sources.list.d/polypack-mcp.list
sudo apt update
sudo apt install polypack-mcp

The repository is updated automatically for each v*.*.* release tag. See docs/apt-repository.md for maintainer setup instructions.

RPM package

RPM-based distributions can install from the public RPM repository:

sudo rpm --import https://imattau.github.io/polypack-mcp/rpm/RPM-GPG-KEY-polypack-mcp
sudo tee /etc/yum.repos.d/polypack-mcp.repo >/dev/null <<'EOF'
[polypack-mcp]
name=Polypack MCP
baseurl=https://imattau.github.io/polypack-mcp/rpm/
enabled=1
gpgcheck=1
gpgkey=https://imattau.github.io/polypack-mcp/rpm/RPM-GPG-KEY-polypack-mcp
EOF
sudo dnf install polypack-mcp

The matching .rpm asset is also attached to the GitHub release:

sudo dnf install ./polypack-mcp-<version>-1.x86_64.rpm

The RPM package provides the same systemd service, store location, localhost Streamable HTTP endpoint, and Python 3.12 requirement as the Debian package.

Run manually

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

The server exposes seventeen focused tools: memory_store, memory_get, memory_update, memory_list_contexts, memory_delete, memory_recall, memory_context, memory_feedback, memory_suppress, memory_supersede, memory_consolidate, memory_link, memory_unlink, memory_thread, memory_store_batch, memory_link_batch, and graph_query. It also publishes context, active-memory, schema, stats, and agent workflow guidance resources under polypack://.

Memory classes are entity, episodic, procedural, and semantic. Store project or user preferences as procedural memories; preference is not a separate memory class.

When using a durable Polypack store, mutating operations checkpoint immediately and the server flushes the store during shutdown.

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.

memory_recall can optionally hydrate related graph memories in the same call:

{
  "query": "identity cache fix",
  "context": "cross-agent",
  "include_neighbors": true,
  "edge_types": ["RESPONDS_TO"],
  "depth": 2,
  "neighbor_limit": 3,
  "limit": 20,
  "token_budget": 4000
}

Neighbor traversal is opt-in and bounded. limit caps the total response and neighbor_limit caps hydrated neighbors; metadata reports moreNeighborsAvailable when additional eligible neighbors were found. Neighbor items include their distance and connecting relationship metadata. Use memory_link with the default RESPONDS_TO relationship for handoffs, reviews, and fixes that address an earlier memory. Graph edges are authoritative for relationships; use graph_query(operation="relationship_diagnostics") to find legacy provenance.responds_to values that are not backed by edges. See polypack://help/workflow for the agent-facing workflow.

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.

Use memory_get for exact ID lookup and memory_update for mutable fields (context, confidence, provenance, and metadata). Content changes should use memory_supersede so history remains intact. Use memory_unlink to correct a relationship and memory_list_contexts to discover namespaces. memory_delete is permanent, requires confirm=true, and supports an optional revision check; prefer memory_suppress when retaining history is useful.

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>=3.3.1 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.

Polypack Memory

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Polypack Memory?

Does Polypack Memory need an API key?

What transport does Polypack Memory use?

When was Polypack Memory last checked?

Documentation

Install and run

Debian package

Optional semantic retrieval

APT repository

RPM package

Run manually

Development

Documentation