Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add udjin-labs/mnemostack --skill claude-codegit clone --depth 1 https://github.com/udjin-labs/mnemostackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/udjin-labs/mnemostack/claude-code)<a href="https://agentmods.dev/skills/udjin-labs/mnemostack/claude-code"><img src="https://agentmods.dev/badge/skills/udjin-labs/mnemostack/claude-code/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/udjin-labs/mnemostack/claude-code"><img src="https://agentmods.dev/badge/skills/udjin-labs/mnemostack/claude-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00612 |
| Opus 5.5 | $0.00000 | $0.00245 |
| Sonnet 5.5 | $0.00000 | $0.00122 |
| Haiku 4.5 | $0.00000 | $0.00061 |
Grade A, and why
claude-code scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Desktop / Claude Code
Wire mnemostack into Claude Desktop (and by extension Claude Code, which reads the same MCP config) as an MCP server.
Install
-
Make sure the binary and a working backend are ready:
pip install 'mnemostack[mcp]' mnemostack health --provider gemini -
Locate the Claude Desktop MCP config:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux (unofficial/Claude Code):
~/.config/claude/claude_desktop_config.json
- macOS:
-
Merge this entry into the
mcpServersblock (create the file if needed):{ "mcpServers": { "mnemostack": { "command": "mnemostack", "args": [ "mcp-serve", "--provider", "gemini", "--collection", "my-memory" ], "env": { "GEMINI_API_KEY": "your-key-here" } } } }Swap
--provider geminiforollamaoropenaiif that's whathealthvalidated. For graph tools, add--memgraph-uri bolt://localhost:7687. -
Restart Claude Desktop (fully quit, not just close the window).
Verify
In a new chat, ask Claude:
List the MCP tools you have available from mnemostack.
You should see health, search, answer, and feedback (plus graph_query
and graph_add_triple if a Memgraph URI was passed). Then:
Use mnemostack to search for "VPN failover" with tier 1.
The reply should cite sources and not leak any snippets (tier 1 = list only).
Uninstall
Remove the mnemostack entry from mcpServers in the config file and restart
Claude Desktop. No other state lives on the host side — the vector store and
the memgraph are owned by the mnemostack process, not by the integration.
Troubleshooting
- Tools don't appear: check Claude Desktop's MCP logs
(
~/Library/Logs/Claude/mcp*.logon macOS). A common cause ismnemostacknot being on PATH for the GUI app — use an absolute path incommand. fastmcp not installed: the[mcp]extra is missing:pip install 'mnemostack[mcp]'.healthsays DOWN: the MCP server will start but every tool call will fail until Qdrant/embedding provider is reachable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 74 lines · 0 tokens per session scan A ede32b744e73
claude-code is a skill published in the GitHub repository udjin-labs/mnemostack (9 stars, last pushed 23d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 612 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
goodmem:mcp
Workflow guide for GoodMem MCP server tools. Use when an agent needs to understand what GoodMem MCP tools are available and how to use them. Parameter signatures are provided by the MCP protocol itself — do not hardcode them here.
goodmem:help
Overview of all available GoodMem skills and what a user needs to get started. Invoke when a user asks what GoodMem skills are available, how to get started, or what they need to set up.
goodmem:java
Use when the user wants to write Java code that interacts with GoodMem - creating embedders, spaces, memories, retrieval, pagination, streaming, or async workflows with the goodmem-java SDK.
goodmem:python
Use when the user wants to write Python code that interacts with GoodMem — creating embedders, spaces, memories, retrieval, managing API keys, etc. Provides the complete SDK reference for the goodmem Python package.
agent-memory-discipline
Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.
memanto-companion
Inspect and manage the cross-session engineering memory that Memanto maintains for your Claude Code skills. Use when the user asks what Memanto remembers, wants to see their engineering profile, manually recall context for a skill, or store a decision. The automatic lifecycle hooks handle capture/injection on their…