EverOS Codex
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 Codexsearch memories about API design decisions"
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 Codex
Use a local EverOS instance as long-term memory for Codex through MCP.
everos-codex provides:
an MCP bridge for local EverOS
repo-scoped default
project_idinferencememory_search,memory_get,memory_save_turn,memory_flusha bundled Codex skill:
everos-local-memory
Why
This project keeps EverOS in its native local shape:
EverOS stays a local HTTP service, usually
http://127.0.0.1:8000Codex connects through MCP over stdio
memory stays local-first
Related MCP server: Codex Memory MCP Server
Install
Verify EverOS is running:
curl http://127.0.0.1:8000/healthInstall the bundled Codex skill:
npx -y everos-codex install-skillAdd this MCP config to ~/.codex/config.toml:
[mcp_servers.everos]
command = "npx"
args = ["-y", "everos-codex"]
[mcp_servers.everos.env]
EVEROS_BASE_URL = "http://127.0.0.1:8000"
EVEROS_APP_ID = "codex"
EVEROS_DEFAULT_PROJECT_ID = ""
EVEROS_AGENT_ID = "codex"
EVEROS_AGENT_NAME = "Codex"
EVEROS_USER_ID = "your-user-id"
EVEROS_USER_NAME = "Your Name"
EVEROS_TIMEOUT_MS = "60000"Restart Codex or open a fresh thread.
Quick checks
npx -y everos-codex doctor
npx -y everos-codex smokeCLI
everos-codex start
everos-codex doctor
everos-codex smoke
everos-codex smoke-e2e
everos-codex install-skillHow project IDs work
If project_id is omitted and EVEROS_DEFAULT_PROJECT_ID is empty, everos-codex infers it from the current repo root name.
Examples:
water->project_id=waterstore-ops-suite->project_id=store-ops-suiteEverOS-Codex->project_id=everos-codex
Explicit project_id still wins.
Bundled skill
This repo bundles skills/everos-local-memory.
Its job is simple:
search before repeating work
save only high-value summaries
verify new memory with
memory_getavoid dumping whole conversations into memory
Acknowledgement
This project is built on top of the open-source EverMind-AI/EverOS project.
Thanks to the EverOS maintainers and contributors for making a local-first memory system available to the community.
License
Apache-2.0
Available Tools
4 toolsmemory_flushC
Manually flush one EverOS session to force extraction.
Inputs: session_id (required), project_id.
memory_getA
List local EverOS memory deterministically. Best for read-your-write checks, recent memory browsing, or session_id-based verification.
Inputs: page, page_size, owner_type, project_id, +3 more.
memory_save_turnA
Save a high-value task summary into local EverOS. Use only for distilled outcomes, not whole chats.
Inputs: summary (required), flush, title, keywords, +2 more.
memory_searchA
Search local EverOS memory for prior coding context. Use for historical fixes, past decisions, or project conventions.
Inputs: query (required), top_k, method, owner_type, +1 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
TDQS
Scored across 4 tools
Each tool targets a distinct memory operation: flush clears session state, get lists memory entries, save_turn stores summaries, and search retrieves past context. No functional overlap.
All tools follow the 'memory_<verb>' pattern, but 'save_turn' includes an object noun, making it slightly less consistent than the single-word verbs. Still, the pattern is clear and predictable.
4 tools is ideal for a focused memory management server. Each tool serves a core function without redundancy or clutter.
The set covers memory flushing, retrieval, saving, and searching. Missing an explicit delete operation, but flush may serve that purpose. Minor gap, but core workflows are supported.
Maintenance
Related MCP Connectors
Shared memory for your AI tools: tasks, notes and context every tool can read and write over MCP.
Hosted agent memory: store, search, and recall facts across sessions from any MCP client.
Persistent memory, knowledge graph, task management and more for AI agents via MCP.
Cross-tool persistent memory and context for AI assistants over MCP.
Related MCP Servers
- AlicenseBqualityCmaintenanceProvides local cross-session memory for Codex by importing transcripts, indexing in SQLite, and exposing search, context, and memory management through MCP tools.13MIT
- AlicenseNot gradedqualityDmaintenanceLocal stdio MCP server for long-term engineering memory, enabling Codex to store, search, and manage project facts, progress, interfaces, and troubleshooting cases.1Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables Codex to automatically recall and persist local project memory—such as decisions, constraints, goals, open loops, and milestones—across sessions via a secure, local MCP adapter.1Apache 2.0
- AlicenseNot gradedqualityBmaintenanceProvides a shared local memory MCP server so multiple coding agents can store, retrieve, and attribute memories across sessions. It enables agents to recall project knowledge and past fixes with provenance.5Apache 2.0