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    bantamkit memory

    1

    Your coding agent stops forgetting: local, offline memory it recalls before it acts. Free, MIT.

    Free

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    bantamkit memory

    bantamkit memory

    Example session with this skill installed

    From now on in this project: React components are function components, and props are declared with interface, never type. Remember that. Also remember why Playwright kept failing at random today: EADDRINUSE because npm run dev was still holding port 3000, fixed with reuseExistingServer: true.

    • Read your context and instructions
    • Compiled the bantamkit memory

    Saved both to project memory.

    What I stored

    ToolMemoryTypeResult
    memory_savereact-interfaces-not-typesfeedbacksaved 'react-interfaces-not-types'
    memory_saveflaky-e2e-is-port-3000-collisionprojectsaved 'flaky-e2e-is-port-3000-collision'

    When I tried to save the React rule a second time under a new name, bantamkit refused and pointed me at the existing memory:

    similar memory 'react-interfaces-not-types' already exists — save under that SAME name to update it, or skip. Do not rename to force a copy.

    Next session: recall before acting

    You ask: "add a Button component with a variant prop". Before I write any code, I check memory:

    memory_recall {"query": "new Button component props"}

[project] [react-interfaces-not-types] (feedback) react component props: function components, typescript interface never type alias
Write React components as functions. Declare props with `interface`, never `type`.
**Why:** the user asked for it on this project.
**How to apply:** new components and any component you touch.

    So the component comes out as function Button({ variant }: ButtonProps) with interface ButtonProps, and you don't have to repeat yourself.

    A week later, CI goes red:

    memory_recall {"query": "playwright tests failing randomly"}

[project] [flaky-e2e-is-port-3000-collision] (project) playwright e2e tests failing randomly EADDRINUSE: dev server already on port 3000
Playwright e2e fails at random with EADDRINUSE when `npm run dev` is still running. Fix: `reuseExistingServer: true` in playwright.config.ts.

    Where it lives

    .bantamkit/memory/facts/react-interfaces-not-types.md is a plain Markdown file with YAML front matter. You can read it, edit it, commit it, or delete it.

    Every tool output above is copied verbatim from a real run of bantamkit-mcp 0.36.0.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Every new session, your coding agent starts from zero. It asks for the same preferences again. It repeats a fix you already found. It forgets the decision you made yesterday.

    bantamkit memory fixes that. It gives your agent a small, durable memory that lives in plain Markdown files in your repo. Your agent checks that memory before it acts, and saves to it whenever you correct it.

    What you get

    • Recall before acting. Before a task that looks like past work, the agent searches memory and gets back the matching facts in full, so it starts from what you already know.
    • Saves the things that matter. Corrections and preferences (feedback), ongoing decisions (project), facts about you (user), and links to dashboards or tickets (reference).
    • No duplicates, no bloat. A save that looks like an existing memory is refused, and the reply names the existing one so the agent updates it instead of piling up copies. memory_compact and memory_dream merge and archive old facts to stay inside a token budget.
    • Plain files you own. Every memory is one readable .md file in .bantamkit/memory/ in your project, with personal facts in ~/.bantamkit/memory/. You can commit them, review them in a PR, or delete them.
    • Private by design. Runs locally over stdio. No account, no API key, and no network calls once it is installed.
    • Optional auto-recall in Claude Code. --install-hooks makes matching memories show up on every prompt, without the agent having to ask.

    Setup (one minute)

    npx -y bantamkit-mcp@0.36.0 --install claude   # or: cursor | copilot | claude-desktop

    Restart your host and the memory tools appear. Node.js 20+ is all you need. A Python build is on PyPI too, as pip install "bantamkit[mcp]".

    Works with

    Claude Code, Claude Desktop, Cursor and VS Code Copilot. It also works with any MCP host that runs a stdio server.

    Open source

    MIT licensed, with source at github.com/Ink01101011/bantamkit. The same tools ship as Node (npm) and Python (PyPI) implementations, and a conformance suite of 17,000+ cases checks that both answer the same way on the same memory store.

    Known limitations

    • Recall matches words, not meaning. Write descriptions in the words you will search with later. The skill teaches your agent to do that.
    • You need to restart your host once after install.
    • It never stores secrets, and never stores things already in your repo or git history.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    • Free to download with an account

    Requires

    Bantamkit MCP
    Node.js 20+

    Listed3 days ago

    What's inside

    Frequently Asked Questions