everos-mcp
Click on "Deploy 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., "@everos-mcpRemember my preferred package manager is pnpm."
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.
EverOS MCP Server
MCP (Model Context Protocol) server wrapping the EverOS memory runtime API. Lets any MCP-compatible coding agent (Claude Code, Cursor, Codex CLI, Gemini CLI, etc.) read and write persistent, Markdown-backed memory.
How It Works
Coding Agent (MCP client)
│ stdio JSON-RPC
▼
everos-mcp (this package) ──HTTP──▶ EverOS REST API (:8000)
│
Markdown + SQLite + LanceDBThe MCP server is a thin shim. It translates MCP tool calls into EverOS REST API requests and formats responses into LLM-friendly text. No state, no caching — the EverOS server is the single source of truth.
Related MCP server: Mycelia
Install
pip install everos-mcp
# or from source:
pip install -e .Requires Python 3.10+.
Prerequisites
A running EverOS server:
everos server start
# Verify: curl http://localhost:8000/health → {"status":"ok"}Register with Coding Agents
Claude Code
Add to ~/.claude/mcp.json or <project>/.claude/mcp.json:
{
"mcpServers": {
"everos": {
"command": "python",
"args": ["-m", "everos_mcp.server"],
"env": {
"EVEROS_API_URL": "http://localhost:8000"
}
}
}
}Cursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"everos": {
"command": "python",
"args": ["-m", "everos_mcp.server"],
"env": {
"EVEROS_API_URL": "http://localhost:8000"
}
}
}
}Codex CLI
codex mcp add everos -- python -m everos_mcp.serverOr set EVEROS_API_URL in Codex's MCP env block.
Generic MCP Host
The server uses stdio transport (JSON-RPC 2.0). Configure with:
Env Var | Default | Description |
|
| EverOS REST API base URL |
| (none) | Bearer token for authenticated EverOS instances |
MCP Tools
everos_memory_add
Add a message to a memory session. Messages accumulate until flushed.
Parameter | Required | Description |
| yes | Who sent the message (e.g., "claude-code", "alice") |
| yes | Message content in plain text or Markdown |
| yes | Session identifier for grouping messages |
| no | "user", "assistant", or "tool" (default: "assistant") |
| no | Owner user ID for scoping |
| no | App scope (default: "default") |
| no | Project scope (default: "default") |
| no | Unix epoch milliseconds (default: now) |
everos_memory_flush
Force memory extraction and indexing for a session.
Parameter | Required | Description |
| yes | Session to flush |
| no | App scope |
| no | Project scope |
everos_memory_search
Hybrid search (keyword + vector) over stored memories.
Parameter | Required | Description |
| yes | Natural language search query |
| no | Search user-track memories (XOR with agent_id) |
| no | Search agent-track memories (XOR with user_id) |
| no | "keyword", "vector", "hybrid", or "agentic" (default: "hybrid") |
| no | Results to return (default: 5, max: 100) |
| no | Include user profile in results |
everos_memory_get
Paginated memory listing without ranking.
Parameter | Required | Description |
| no | Owner user ID (XOR with agent_id) |
| no | Owner agent ID (XOR with user_id) |
| no | "episode", "profile", "agent_case", or "agent_skill" |
| no | Page number (default: 1) |
| no | Items per page (default: 20, max: 100) |
everos_health
Check EverOS server connectivity. No parameters.
Example Usage (via Claude Code)
Once registered, Claude Code can use these tools directly:
User: "Remember that I prefer pnpm over npm for this project."
Claude calls: everos_memory_add(sender_id="alice", content="Prefers pnpm over npm",
role="user", session_id="<current>")
User (next session): "Set up the package scripts for me."
Claude calls: everos_memory_search(query="package manager preference", user_id="alice")
→ "Prefers pnpm over npm" found — uses pnpm without re-askingWhere Memories Live
All memories are stored as Markdown files in ~/.everos/:
~/.everos/
default/default_project/users/alice/
user.md # user profile
episodes/episode-2026-07-14.md # daily conversation logYou can read, edit, and version-control these files directly.
Development
# Install with dev deps
pip install -e ".[dev]"
# Run tests
pytest src/everos_mcp/tests/ -v
# Manual smoke test (requires running EverOS)
EVEROS_API_URL=http://localhost:8000 python -m everos_mcp.serverLicense
Apache 2.0 — same as EverOS.
This server cannot be deployed
Maintenance
Related MCP Connectors
Hosted MCP memory for coding agents: persistent across sessions, editable markdown, team sharing.
Persistent memory, knowledge graph, task management and more for AI agents via MCP.
One memory, every AI. A shared, user-owned markdown memory your AI clients read and write over MCP.
Persistent memory for AI agents across Claude, ChatGPT and any MCP client.
Related MCP Servers
- AlicenseBqualityDmaintenanceLocal Markdown-backed memory tools for Codex and other MCP-capable agents. Exposes durable agent knowledge via CLI and MCP server.5MIT
- AlicenseNot gradedqualityDmaintenanceProvides a persistent, cross-tool memory layer for AI coding agents via MCP, enabling storage and retrieval of decisions, preferences, and context across different tools and models.1 npm1MIT
- AlicenseNot gradedqualityDmaintenanceProvides portable memory for AI agents using plain Markdown files. Enables storing, recalling, and managing memories via MCP tools like recall, remember, forget, list, and get.3 npm1MIT
- AlicenseNot gradedqualityBmaintenanceProvides persistent, local-first memory for coding agents with Markdown as the source of truth, exposed via CLI, loopback API, MCP, and Codex hooks for context retrieval and durable writes.MIT