anchor-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., "@anchor-mcpshow my active task"
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.
anchor-mcp
A portable agent working state server. Any AI coding agent drops anchor here.
Anchor is an MCP server that manages persistent working state for AI coding agents — tasks, plans, scratch notes, learnings, and project rules. It works with Claude Code, OpenCode, Codex CLI, Cursor, Windsurf, or any MCP-compatible agent.
Why?
Every AI coding tool has its own proprietary state directory (.claude/,
.codex/, .opencode/). None of them share state. Anchor gives every agent
a shared home base — the same active task, the same plans, the same memory —
regardless of which tool you're using.
What it stores
Per git worktree, Anchor manages:
Active task — what you're working on right now
Plans — execution blueprints with linked issues and learnings
Notepads — freeform scratch notes by topic
Memory — tagged learnings, decisions, and patterns
Rules — project-specific agent instructions
Quick start
Install
npm install -g anchor-mcpConfigure (Claude Code)
Add to .claude/.mcp.json:
{
"mcpServers": {
"anchor": {
"command": "anchor-mcp"
}
}
}Configure (OpenCode)
Add to ~/.config/opencode/opencode.json:
{
"mcp": {
"anchor": {
"type": "local",
"command": ["anchor-mcp"],
"enabled": true,
"environment": {}
}
}
}Configure (Codex CLI)
Add to .codex/config.toml:
[mcp_servers.anchor]
command = "anchor-mcp"Configure (Cursor / Windsurf)
Add to your MCP server settings:
{
"anchor": {
"command": "anchor-mcp"
}
}Tools
Anchor provides 6 grouped tools. Each tool accepts an action parameter:
Tool | Actions | Description |
|
| Manage the active task and task list |
|
| Manage execution plans with issues and learnings |
|
| Manage freeform scratch notes by topic |
|
| Store and retrieve learnings, decisions, patterns |
|
| Manage project-specific agent instructions |
| (single action) | Promote plan learnings into project rules |
Usage examples
Set an active task:
task_manager(action="set_active", description="Implement user authentication")Save a plan:
plan_manager(action="save", name="auth-flow", content="# Auth Flow Plan\n\n1. Add login endpoint\n2. Add JWT middleware")Add a memory:
memory_manager(action="add", content="Always use httpOnly cookies for JWT", tags=["auth", "security"])Search memories:
memory_manager(action="search", query="authentication")State directory
Anchor stores state in .anchor/ at your project root:
.anchor/
├── state.json # Active task + task list (gitignored)
├── plans/
│ └── {plan-name}/
│ ├── plan.md
│ ├── issues.md
│ └── learnings.md
├── notepads/
│ └── {topic}.md
├── memory.jsonl
└── rules.mdPlans, notepads, rules, and memory are designed to be committed to git.
state.json is machine-specific and should be gitignored.
License
MIT
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