Model Context Protocol server for Agents Remember.
Project description
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: github.com/Foxfire1st/agents-remember-md
Quickstart
Setup is agent-driven. Ask your agent to:
- Install and wire Agents Remember MCP — set it to run via
uvx agents-remember-mcp --config <absolute-path>/agents-remember-settings.json, help you fill in that settings file (starter below), and register it with this harness. Then restart the harness so it loads the server. - Install Agents Remember — run
runtime_install, thenskills_install(scaffolding, skills, and — if providers are enabled and Docker is running — the provider images). - Onboard your project — run the
C-13-install-and-onboardskill: it pre-checks the setup, installs the start hook (or places the directive for harnesses without one), sets up the memory repo (it will ask: scaffold a new one or use an existing one), bootstraps onboarding, and starts the providers indexing your code and memory.
The only hands-on steps for you: ask, restart once after step 1, and answer the new-vs-existing memory question in step 3.
Requirements
- Python 3.11 or newer
- an MCP-capable coding harness
- uv (for
uvx) or pip - Git for repository and memory ledger operations
- Docker when provider tools are enabled (plus Ollama for the grepai embedder)
Install And Run
The simplest path is uvx, which fetches and runs the server on demand — no
manual virtualenv or PATH setup:
uvx agents-remember-mcp --config /absolute/path/to/agents-remember-settings.json
Or install with pip and use the console command:
python -m pip install agents-remember-mcp
agents-remember-mcp --config /absolute/path/to/agents-remember-settings.json
The config path must be absolute, and the settings file must live outside the
ar-coordination/ runtime folder.
Settings
A minimal starter agents-remember-settings.json (your agent can fill this in):
{
"version": 1,
"coordinationRoot": "/absolute/path/to/ar-coordination",
"workspaceRoot": "/absolute/path/to/workspace",
"repositories": {
"<your-repo-name>": {}
},
"providers": {
"codegraphcontext-code": {},
"grepai-memory": {}
}
}
coordinationRoot is where the runtime and memory repos live (populated by
runtime_install). workspaceRoot holds your code repos. List each repo you
want Agents Remember to manage under repositories. Omit or empty the
providers block if you do not want the Docker-backed providers. Full field
reference:
settings-json.md.
Harness Setup
Register the MCP server with your harness by pointing it at uvx (or the
installed console command) and the absolute settings path:
{
"command": "uvx",
"args": [
"agents-remember-mcp",
"--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.
First Operations
For a new workspace, the usual first MCP calls (Quickstart step 2) are:
server_info()
runtime_install(dry_run=false)
skills_install(dry_run=false)
context_packet(repo_id="<repo-id>", include_providers=true)
Then run the installed C-13-install-and-onboard skill (Quickstart step 3) to
install the start hook, set up the memory repo, bootstrap onboarding, and start
provider indexing.
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. Full tool list: MCP Tool Reference.
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