bantamkit

Name: bantamkit
Author: Ink01101011

Verified

Persistent memory for coding agents: an MCP server for Claude Code, Claude Desktop, Cursor and VS Code Copilot. Install once from npm or PyPI, then it runs offline.

1stars

1forks

Python

Added 10/20/2026

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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.

Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.

Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.

Read the Terms of Service

AI Agentsagentagent-memoryai-agentsclaudeclaude-codeclaude-code-hooksclaude-desktopcopilotcursorgithub-copilotjson-schemallmmcpmcp-servermemorymodel-context-protocolnodejspersistent-memorypythonvscode

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Maintainer of this skill?

Automated security scan — not a certification.

Installation

# Add to your Claude Code skills
git clone https://github.com/Ink01101011/bantamkit

Getting Started

Guides for using ai agents skills like bantamkit.

Security ReportVerified

Last scanned: 10/20/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-10-20T09:10:58.235Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

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README.md

bantamkit — memory MCP server for Claude Code, Cursor, VS Code Copilot and Claude Desktop

Give your coding agent a memory that outlasts the session. bantamkit is an MCP server: the agent saves what is worth keeping — a preference you stated, a decision, the fix that worked — and recalls it next session instead of asking you again. It works with Claude Code, Claude Desktop, Cursor, GitHub Copilot in VS Code and any stdio MCP client. Install it once from npm or PyPI; after that it starts offline.

🚀 Quick start

npx -y bantamkit-mcp@latest --install claude   # or claude-desktop, copilot, cursor

Then restart the host (in Claude Code, open a new session) and ask the agent to call bantamkit_status. Prefer Python? pip install "bantamkit[mcp]" into a venv you keep, then bantamkit-mcp --install claude. Every route and host is below.

✨ What you get

Memory that persists. Facts are plain Markdown files under .bantamkit/memory, deduped and held to a byte budget. memory_save and memory_recall do the work; memory_compact and memory_dream keep the store tidy.
Layered by default. Recall reads the project store, any stores you grant in .bantamkit/config.yaml, and your profile store ~/.bantamkit/memory. Saves go to the project store.
One command per host. --install writes the entry for Claude Code, Claude Desktop, Cursor or VS Code Copilot, backs up any file it edits, and never prompts.
Offline after one install. Both install routes record the server by absolute path, so no launch needs the network or your shell's PATH.
Claude Code hooks, if you want them. --install-hooks puts the memory index in front of each new session, surfaces matching facts on each prompt, and nudges a save at the end of a long session that saved nothing (docs/hooks.md).
More than memory. JSON Schema validation, a token ledger read off the host's transcripts, a skill-catalogue audit, and shift-work tools that plan and hand off multi-step jobs — the fifteen tools.
Two runtimes, one store. Pure Node on npm and Python on PyPI read and write the same files, and every surface is compared between both runtimes by a conformance suite (node tools/conformance/run.mjs --all).
A Python library for small models, too. pip install bantamkit lifts small-model agents (~1B–8B, any OpenAI-compatible endpoint): malformed output, unreviewed answers, forgotten context and runaway loops are absorbed by code, and a bundled eval suite measures the uplift.

📑 Contents

Topic	What you'll find
Install the MCP server	Three ways to set it up — pick one
Install once, run offline (recommended)	One command; later launches need no network
Run with npx at every launch	The online form, and why it hangs offline
Install with Python (PyPI)	A venv you keep; a wheelhouse for no-network machines
Connect to a host	The same five steps for every host
Connect to Claude Code	`--install claude`, `claude mcp list`, `claude mcp remove`
Connect to Claude Desktop	`claude_desktop_config.json` per OS
Connect to Cursor	`~/.cursor/mcp.json`
Connect to VS Code (GitHub Copilot)	`mcp.json` with the `servers` key
Connect other MCP clients	Codex and any stdio host
Configuration	Every flag and environment variable, with its default
Update	`--update`, then restart the server
Troubleshooting	Timeouts, Connection closed, refusals, the wrong store
What it serves	15 tools, one prompt, two resource templates
Use it as a Python library	`pip install bantamkit` and a minimal agent
Recommended defaults	Which components to attach, measured on four models
Documentation	Every page under `docs/`
Repo layout	What lives where

📥 Install the MCP server

Two implementations of one server — Node on npm, Python on PyPI — share one memory store on disk. To just try it:

npx -y bantamkit-mcp --assets-root              # Node, no Python required
pipx run --spec "bantamkit[mcp]" bantamkit-mcp --assets-root   # Python

A host launches the server every session, so what matters is whether each launch needs the network. Pick one of the three ways below.

Install once, run offline (recommended)

npx -y bantamkit-mcp@latest --install claude   # or claude-desktop, copilot, cursor

This runs npm install --prefix ~/.bantamkit/mcp once and records <the node that ran it> ~/.bantamkit/mcp/node_modules/bantamkit-mcp/dist/cli.js, both absolute. No later launch needs npx, the registry or your PATH, and it never downgrades a newer kept install.

The recorded node is one version of node. Switch away from it and re-run with --force.
Replacing an old npx entry needs --force (Claude Code: claude mcp remove first).
Installing into another host while offline: plain npx -y hangs before bantamkit starts. Use npx --offline -y bantamkit-mcp@<version> --install <host>, or the kept install's own CLI: <node> ~/.bantamkit/mcp/node_modules/bantamkit-mcp/dist/cli.js --install <host>.

Measurements: docs/install.md → MCP server: measured install detail.

Run with npx at every launch

{"mcpServers": {"bantamkit": {"command": "npx", "args": ["-y", "bantamkit-mcp"]}}}

This asks the registry on every launch. Offline it fails silently: with a warm cache, npx -y bantamkit-mcp, npx -y bantamkit-mcp@latest and a pinned version each hung to the 45 s bound with 0 bytes on stdout, and the host reports only its own handshake timeout. npx also caches what latest resolved to, so add @latest or pin a version (why).

Install with Python (PyPI)

pip install "bantamkit[mcp]"            # into a venv you keep, not a pipx run
bantamkit-mcp --install claude          # or claude-desktop, copilot, cursor

--install records the venv's console script by absolute path with "args": [], so no launch needs the network. With no network at all, pip download a wheelhouse on a machine with the same OS, CPU architecture and Python version, then pip install --no-index --find-links: steps.

🔌 Connect to a host

--install <host> (claude, claude-desktop, copilot, cursor) writes the entry. It backs the file up first, refuses an entry that differs unless you pass --force, and never prompts — so it behaves the same in a terminal, in CI and inside another agent. With Python, run bantamkit-mcp --install <host> from your venv instead of the npx line.

Each host below has the same steps: 1 command, 2 file, 3 entry, 4 confirm, 5 undo or re-run. The entry's command and args depend on the install route:

Route	`command`	`args`
npm, install once	`/absolute/path/to/node`	`["/Users/you/.bantamkit/mcp/node_modules/bantamkit-mcp/dist/cli.js"]`
Python venv	`/absolute/path/to/env/bin/bantamkit-mcp`	`[]`
npx every launch	`npx`	`["-y", "bantamkit-mcp"]`

For JSON hosts, a quick check of the recorded command: run it in a terminal — with nothing on stdin it prints usage: bantamkit-mcp … and exits 0.

Connect to Claude Code

Command: npx -y bantamkit-mcp@latest --install claude
File: none edited directly — it runs claude mcp add bantamkit -s user -- <command> <args> (user scope, every project), because ~/.claude.json also holds host state that is not MCP config.
Entry: printed as ran : claude mcp add bantamkit -s user -- <node> <cli.js>.
Confirm: claude mcp list prints bantamkit: <node> <cli.js> - ✔ Connected (Claude Code 2.1.272; run it outside a project whose .mcp.json also names bantamkit, or it prints [Conflicting scopes]). In a session, ask the agent to call bantamkit_status.
Undo / re-run: --force does not reach Claude Code, and a second add fails with MCP server bantamkit already exists in user config. Remove first:
```
claude mcp remove bantamkit -s user
npx -y bantamkit-mcp@latest --install claude
```

Connect to Claude Desktop

Command: npx -y bantamkit-mcp@latest --install claude-desktop
File: macOS ~/Library/Application Support/Claude/claude_desktop_config.json · Windows `%APPDATA%\Claude\claude_deskto

Frequently Asked Questions

What is bantamkit?

bantamkit is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Ink01101011. Persistent memory for coding agents: an MCP server for Claude Code, Claude Desktop, Cursor and VS Code Copilot. Install once from npm or PyPI, then it runs offline. It has 1 GitHub star.

Is bantamkit safe to use?

Yes. bantamkit passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install bantamkit?

Clone the repository with "git clone https://github.com/Ink01101011/bantamkit" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is bantamkit written in?

bantamkit is primarily written in Python. It is open-source under Ink01101011 on GitHub, so you can review or fork the full source.

Are there alternatives to bantamkit?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh bantamkit against similar tools.

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bantamkit — memory MCP server for Claude Code, Cursor, VS Code Copilot and Claude Desktop

🚀 Quick start

npx -y bantamkit-mcp@latest --install claude   # or claude-desktop, copilot, cursor

✨ What you get

Memory that persists. Facts are plain Markdown files under .bantamkit/memory, deduped and held to a byte budget. memory_save and memory_recall do the work; memory_compact and memory_dream keep the store tidy.
Layered by default. Recall reads the project store, any stores you grant in .bantamkit/config.yaml, and your profile store ~/.bantamkit/memory. Saves go to the project store.
One command per host. --install writes the entry for Claude Code, Claude Desktop, Cursor or VS Code Copilot, backs up any file it edits, and never prompts.
Offline after one install. Both install routes record the server by absolute path, so no launch needs the network or your shell's PATH.
Claude Code hooks, if you want them. --install-hooks puts the memory index in front of each new session, surfaces matching facts on each prompt, and nudges a save at the end of a long session that saved nothing (docs/hooks.md).
More than memory. JSON Schema validation, a token ledger read off the host's transcripts, a skill-catalogue audit, and shift-work tools that plan and hand off multi-step jobs — the fifteen tools.
Two runtimes, one store. Pure Node on npm and Python on PyPI read and write the same files, and every surface is compared between both runtimes by a conformance suite (node tools/conformance/run.mjs --all).
A Python library for small models, too. pip install bantamkit lifts small-model agents (~1B–8B, any OpenAI-compatible endpoint): malformed output, unreviewed answers, forgotten context and runaway loops are absorbed by code, and a bundled eval suite measures the uplift.

📑 Contents

Topic	What you'll find
Install the MCP server	Three ways to set it up — pick one
Install once, run offline (recommended)	One command; later launches need no network
Run with npx at every launch	The online form, and why it hangs offline
Install with Python (PyPI)	A venv you keep; a wheelhouse for no-network machines
Connect to a host	The same five steps for every host
Connect to Claude Code	`--install claude`, `claude mcp list`, `claude mcp remove`
Connect to Claude Desktop	`claude_desktop_config.json` per OS
Connect to Cursor	`~/.cursor/mcp.json`
Connect to VS Code (GitHub Copilot)	`mcp.json` with the `servers` key
Connect other MCP clients	Codex and any stdio host
Configuration	Every flag and environment variable, with its default
Update	`--update`, then restart the server
Troubleshooting	Timeouts, Connection closed, refusals, the wrong store
What it serves	15 tools, one prompt, two resource templates
Use it as a Python library	`pip install bantamkit` and a minimal agent
Recommended defaults	Which components to attach, measured on four models
Documentation	Every page under `docs/`
Repo layout	What lives where

📥 Install the MCP server

Two implementations of one server — Node on npm, Python on PyPI — share one memory store on disk. To just try it:

npx -y bantamkit-mcp --assets-root              # Node, no Python required
pipx run --spec "bantamkit[mcp]" bantamkit-mcp --assets-root   # Python

A host launches the server every session, so what matters is whether each launch needs the network. Pick one of the three ways below.

Install once, run offline (recommended)

npx -y bantamkit-mcp@latest --install claude   # or claude-desktop, copilot, cursor

The recorded node is one version of node. Switch away from it and re-run with --force.
Replacing an old npx entry needs --force (Claude Code: claude mcp remove first).
Installing into another host while offline: plain npx -y hangs before bantamkit starts. Use npx --offline -y bantamkit-mcp@<version> --install <host>, or the kept install's own CLI: <node> ~/.bantamkit/mcp/node_modules/bantamkit-mcp/dist/cli.js --install <host>.

Measurements: docs/install.md → MCP server: measured install detail.

Run with npx at every launch

{"mcpServers": {"bantamkit": {"command": "npx", "args": ["-y", "bantamkit-mcp"]}}}

Install with Python (PyPI)

pip install "bantamkit[mcp]"            # into a venv you keep, not a pipx run
bantamkit-mcp --install claude          # or claude-desktop, copilot, cursor

🔌 Connect to a host

Each host below has the same steps: 1 command, 2 file, 3 entry, 4 confirm, 5 undo or re-run. The entry's command and args depend on the install route:

Route	`command`	`args`
npm, install once	`/absolute/path/to/node`	`["/Users/you/.bantamkit/mcp/node_modules/bantamkit-mcp/dist/cli.js"]`
Python venv	`/absolute/path/to/env/bin/bantamkit-mcp`	`[]`
npx every launch	`npx`	`["-y", "bantamkit-mcp"]`

For JSON hosts, a quick check of the recorded command: run it in a terminal — with nothing on stdin it prints usage: bantamkit-mcp … and exits 0.

Connect to Claude Code

Command: npx -y bantamkit-mcp@latest --install claude
File: none edited directly — it runs claude mcp add bantamkit -s user -- <command> <args> (user scope, every project), because ~/.claude.json also holds host state that is not MCP config.
Entry: printed as ran : claude mcp add bantamkit -s user -- <node> <cli.js>.
Confirm: claude mcp list prints bantamkit: <node> <cli.js> - ✔ Connected (Claude Code 2.1.272; run it outside a project whose .mcp.json also names bantamkit, or it prints [Conflicting scopes]). In a session, ask the agent to call bantamkit_status.
Undo / re-run: --force does not reach Claude Code, and a second add fails with MCP server bantamkit already exists in user config. Remove first:
```
claude mcp remove bantamkit -s user
npx -y bantamkit-mcp@latest --install claude
```

Connect to Claude Desktop

Command: npx -y bantamkit-mcp@latest --install claude-desktop
File: macOS ~/Library/Application Support/Claude/claude_desktop_config.json · Windows `%APPDATA%\Claude\claude_deskto