agent-checkpoint-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agent-checkpoint-mcpresume my last session checkpoint"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
agent-checkpoint-mcp
Never lose your place when an AI agent session gets cut off.
A tiny, 100% local MCP server that saves work-in-progress checkpoints to SQLite. When a session dies mid-plan — context limit hit, quota exhausted, laptop closed — the next session (same agent or a different one: Claude Code, Codex, Cursor) reads the exact state and continues from the last sub-task instead of redoing work.
Local-first: SQLite on your machine. No network calls, no API keys, no LLM, zero cost.
Cross-agent: checkpoints are keyed by project directory, so Claude Code can resume what Codex started.
Cross-platform: macOS (incl. Apple Silicon), Linux, Windows. Python 3.11+, single dependency (
mcp).
The problem
You're 40 minutes into a 6-step plan. The session hits the context limit and compacts — or your quota runs out and you switch agents. The new session sees the plan, maybe, but not that step 3 was half done: the migration file was written but not applied, two of five tests were fixed. So it starts step 3 over. This server makes "exactly where were we?" a tool call.
Related MCP server: mcp-taskflow
Install (one command)
macOS / Linux
curl -fsSL https://raw.githubusercontent.com/DiegoWare/agent-checkpoint-mcp/main/install/install.sh | bashWindows (PowerShell)
irm https://raw.githubusercontent.com/DiegoWare/agent-checkpoint-mcp/main/install/install.ps1 | iexThat single command does everything:
Installs the package with
uv,pipx, orpip --user(whichever you have).Detects installed agents — Claude Code, Cursor, Codex — and registers the server in each one's MCP config (non-destructively).
Installs the Claude Code recovery hooks (see below): every new, resumed, or compacted session automatically receives the latest checkpoint, and an emergency checkpoint is saved right before every compaction.
Prints what it changed. Restart your agent and everything is live.
Re-running the installer upgrades and re-registers.
Don't want a piece of it? Everything is reversible with one command:
agent-checkpoint-mcp uninstall --hooks # remove the Claude Code hooks only
agent-checkpoint-mcp uninstall --mcp # remove the MCP registrations only
agent-checkpoint-mcp uninstall # remove both(Or skip hooks at install time: AGENT_CHECKPOINT_NO_HOOKS=1 curl ... | bash,
and agent-checkpoint-mcp setup --no-hooks thereafter. --dry-run previews
any of these without writing.)
Prefer manual control end to end?
pipx install agent-checkpoint-mcp # or: uv tool install agent-checkpoint-mcp
agent-checkpoint-mcp setup # same as the installer's registration stepDocker-isolated install (Agent Checkpoint + Codebase Memory)
If you do not want either MCP installed into the host Python environment, this repository includes an optional Docker path for macOS and Linux. From a clone of this repository, run:
./install/docker.sh installThat one command builds a local agent-checkpoint-mcp:local image containing
this project and the checksum-verified
codebase-memory-mcp
v0.8.1 binary, then registers both servers with detected Claude Code, Cursor,
and Codex installations. The clients launch one short-lived stdio container
per MCP connection; there are no background services or open ports.
At runtime each container has no network, runs as a non-root user with dropped
capabilities, and sees only the active Git repository at its original absolute
path. The repository mount and container root are read-only. Checkpoints and
code indexes persist in separate Docker volumes, so Codebase Memory cannot
create .codebase-memory/graph.db.zst or otherwise edit source files.
Manage either MCP independently:
./install/docker.sh disable codebase # keep Agent Checkpoint
./install/docker.sh enable codebase
./install/docker.sh disable checkpoint # also removes its Claude hooks
./install/docker.sh enable checkpoint
./install/docker.sh doctor # config + stdio handshake checks
./install/docker.sh uninstall # keep image and persistent dataDisabling or uninstalling never deletes data. Purging is separate and requires an explicit confirmation flag:
./install/docker.sh purge checkpoint --yes
./install/docker.sh purge codebase --yes
./install/docker.sh purge all --yesThe registrations point to the launcher inside this checkout, so keep the clone at the same path. Docker limits accidental host exposure, but anyone who controls the Docker daemon or the host root account can still access Docker volumes and mounts.
Or register by hand — the server command is just agent-checkpoint-mcp:
// Claude Code (~/.claude.json) and Cursor (~/.cursor/mcp.json)
{ "mcpServers": { "agent-checkpoint": { "command": "agent-checkpoint-mcp", "args": [] } } }# Codex (~/.codex/config.toml)
[mcp_servers.agent-checkpoint]
command = "agent-checkpoint-mcp"
args = []Tools
Tool | What it does |
| Save progress. Designed to be called after every sub-task (a file edited, a test passing), not just when a numbered step completes. |
| The latest checkpoint for this project, formatted as a resume brief: current step, what's done (don't redo), the exact next action, remaining steps. |
| Session history with timestamps, newest first. |
| Wipe this project's history. Dry-run by default; requires |
All tools take an optional project_dir override. By default the project is
detected from the server's working directory, walking up to the nearest
.git root — so checkpoints saved from repo/src/ and repo/ land in the
same bucket, and different projects never mix.
Example flow
Session A (Claude Code, dies at context limit):
save_checkpoint(plan="1. Schema\n2. Endpoints\n3. Tests", current_step=2,
total_steps=3, step_status="in_progress",
what_was_done="- schema migrated\n- POST /users done",
what_remains="- GET /users/:id handler, then wire router")
Session B (Codex, next morning):
get_checkpoint()
→ # Resume point — step 2/3 (in_progress)
## What was already done (do NOT redo this) ...
## What remains in the current step — continue HERE ...How recovery works
Two mechanisms, both installed automatically by the one-command installer:
Claude Code hooks (installed for you)
The installer merges two hooks into ~/.claude/settings.json
(non-destructively — your existing hooks are untouched):
SessionStart(startup|resume|compact) runsagent-checkpoint-mcp show, which prints the latest checkpoint — Claude Code injects that output into the fresh context. The resuming agent knows where it left off without even calling a tool. This is the main recovery mechanism.PreCompactrunsagent-checkpoint-mcp precompact-snapshot, which parses the session transcript locally (last todo-list state + last assistant messages) and stores an emergency checkpoint right before compaction. Honest caveat: hooks can't force the model to call an MCP tool, so this snapshot is reconstructed from the transcript — cruder than a propersave_checkpoint, but it means even a session that never saved manually leaves a trail.
Remove them anytime with agent-checkpoint-mcp uninstall --hooks. To merge
them by hand instead (e.g. per-project in .claude/settings.json), use
examples/claude-settings-hooks.json.
Per-project instructions (one command per project)
For the best checkpoints — saved deliberately after every sub-task, not just recovered from transcripts — run this once inside a project:
agent-checkpoint-mcp initIt appends a checkpoint-discipline section to the project's CLAUDE.md and
AGENTS.md (creating them if needed, skipping if already present). The key
rule it teaches: save after every concrete sub-task, and call
get_checkpoint first when a task looks like a continuation. Prefer to copy
by hand? See examples/.
Where data lives
One SQLite database, keyed by project path — nothing is written inside your repos:
OS | Path |
macOS |
|
Linux |
|
Windows |
|
The Docker variant stores checkpoints in the
agent-checkpoint-mcp-checkpoints volume and Codebase Memory indexes in the
agent-checkpoint-mcp-codebase volume.
Override with the AGENT_CHECKPOINT_HOME environment variable.
CLI
agent-checkpoint-mcp # run the MCP server (stdio) — what agent configs execute
agent-checkpoint-mcp show [--project D] # print the latest checkpoint (used by the SessionStart hook)
agent-checkpoint-mcp list [--project D] # checkpoint history
agent-checkpoint-mcp clear [--yes] # delete this project's checkpoints
agent-checkpoint-mcp init [--project D] # add checkpoint instructions to CLAUDE.md/AGENTS.md
agent-checkpoint-mcp setup [--no-hooks] # (re)register with detected agents + install hooks
agent-checkpoint-mcp uninstall [--hooks|--mcp] # remove what setup installed
agent-checkpoint-mcp precompact-snapshot # used by the PreCompact hook (hook JSON on stdin)setup and uninstall accept --dry-run to preview changes without writing.
Development
git clone https://github.com/DiegoWare/agent-checkpoint-mcp
cd agent-checkpoint-mcp
python3 -m venv .venv && .venv/bin/pip install -e '.[dev]'
.venv/bin/pytestLicense
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-qualityCmaintenanceA local-first MCP server providing persistent, searchable knowledge base via SQLite, enabling AI agents to save and recall facts across sessions without cloud dependencies.Last updatedMIT
- Alicense-qualityDmaintenanceA local MCP server that gives AI agents structured task planning, execution tracking, and guided research workflows.Last updated13MIT
- Alicense-qualityDmaintenanceA lightweight MCP server that gives AI assistants persistent, shared memory across sessions and team members, backed by a single SQLite database. It enables saving, searching, and retrieving observations and project context to maintain continuity and team knowledge.Last updated3MIT
- Alicense-qualityDmaintenanceA local MCP server that gives AI coding agents persistent memory and context across sessions.Last updated7MIT
Related MCP Connectors
Cloud-hosted MCP server for durable AI memory
Person-owned, portable AI memory as a remote MCP server, readable and writable by any MCP client.
Driflyte MCP server which lets AI assistants query topic-specific knowledge from web and GitHub.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/DiegoWare/agent-checkpoint-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server