agents-remember-mcp 0.2.0

Model Context Protocol server for Agents Remember.

Agents Remember MCP

agents-remember-mcp is the installable Model Context Protocol server for Agents Remember. It lets an MCP-capable coding harness call Agents Remember operations from the host instead of asking the model to edit or execute coordinator scripts directly.

Source checkout: github.com/Foxfire1st/agents-remember-md

The full project documentation lives one directory up in the source checkout:

• Agents Remember README
• Getting Started
• Settings Reference

Requirements

• Python 3.11 or newer
• an MCP-capable coding harness
• Git for repository and memory ledger operations
• Docker when provider tools are enabled

Install

Install from PyPI:

python -m pip install agents-remember-mcp

The installed console command is:

agents-remember-mcp --config /absolute/path/to/agents-remember-settings.json

The config path must be absolute. The MCP authority settings file must live outside the ar-coordination/ runtime folder. A starter settings file is available in the source checkout at examples/mcp/settings.example.json.

Harness Setup

Register the MCP server with your harness by pointing it at the installed command and the trusted settings file:

{
  "command": "agents-remember-mcp",
  "args": [
    "--config",
    "/absolute/path/to/agents-remember-settings.json"
  ]
}

After installing or changing the MCP server registration, restart the harness so it reloads the server and discovers the tool list.

Once the MCP server is running, ask your model to use Agents Remember. Normal use should be agent-driven through MCP tool calls; manual tool calls are mainly for setup and troubleshooting.

First Operations

For a new workspace, the usual first MCP calls are:

server_info()
runtime_install(dry_run=false)
skills_install(dry_run=false)
context_packet(repo_id="<repo-id>", include_providers=true)

Then ask the model to initialize memory for the target repository and bootstrap onboarding through the installed Agents Remember skills.

Tool Surface

The server exposes tools for:

• startup context and drift checks
• runtime and skill installation
• memory initialization, memory quality checks, and route index refresh
• provider status, watcher control, GrepAI search, and CodeGraphContext queries
• chat/direct closeout and worktree-backed task workflows
• benchmark preparation and execution

Provider tools only work when the MCP settings enable the provider and the required Docker services are available.