How do I install Kortexio Memory?

Copy the http config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Kortexio Memory need an API key?

No required environment variable is listed on this record.

What transport does Kortexio Memory use?

Kortexio Memory is reached over HTTP.

When was Kortexio Memory last checked?

Last checked 2026-11-10. Hosted ambient memory for AI agents. Retrieve context and save notes via MCP tools with OAuth.

Kortexio Memory MCP server

Power your agent

Add this server

The publisher's own URL. Not a PlugMCP endpoint.

Add to Cursor Add in Claude Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Server URL

https://mcp.kortexio.io/{appId}/mcp

The Claude button above opens Claude with the name and URL filled in. You still confirm it there.

shClaude Code

1claude mcp add --transport http io.kortexio-memory https://mcp.kortexio.io/{appId}/mcp

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.kortexio-memory": {4      "command": "npx",5      "args": [6        "-y",7        "mcp-remote",8        "https://mcp.kortexio.io/{appId}/mcp"9      ]10    }11  }12}

claude_desktop_config.json

Remote · HTTPPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Remote

Transport: http
Version: 1.0.0
Last checked

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

Try it in three commands

git clone https://github.com/Kortexio/ContextMemory.git && cd ContextMemory
docker compose -f docker-compose.yml -f docker-compose.llamacpp.yml up --build -d   # CPU; GPU: docker-compose.vllm.yml
./scripts/aha-chat.sh                                                             # Windows: .\scripts\aha-chat.ps1

aha-chat sends two requests in the same session. The second one carries only the new question:

==> Turn 1: "Remember this for later: our staging database host is postgres-staging-01."
==> Turn 2: "What is our staging database host?"   (no history in the request body)
AHA OK — the client sent no history; the gateway remembered 'postgres-staging-01'.

The same check runs in CI against a real llama-server on every push (e2e-llamacpp). First start downloads a ~2 GB GGUF; pick another model with LLAMACPP_HF_MODEL (Engines). Admin UI: http://localhost:5200.

What is ContextMemory?

ContextMemory is the open-source agentic memory gateway behind Kortexio.

Your app (or Cursor/Claude) keeps talking to a normal chat API. The gateway:

Authenticates the tenant and attaches session wiki + history
Runs an agentic tool loop when tools are enabled (wiki search, sandbox, MCP, …)
Applies skills, guardrails, validators, and optional HITL before destructive actions
Returns a standard OpenAI-shaped chat.completions response (streaming supported)

Your client (OpenAI SDK / Cursor MCP / curl)
        │
        ▼  POST /v1/chat/completions
┌────────────────────────────────────────────┐
│  ContextMemory (.NET 9)                    │
│  Auth · session wiki · Global Wiki tool    │
│  Agentic loop · skills · guardrails · HITL │
│  LLM backend (per app — BYO engine)        │
└───────┬──────────────────┬─────────────────┘
        ▼                  ▼
 sandbox-runtime      mcp-runtime / MCP servers
 (shell/python/node)  (HTTP + stdio, OAuth)
 or Azure ACA sessions

Honest boundaries: this is a gateway + server-side harness, not a client agent framework (LangGraph/CrewAI) and not an agent OS (Letta). You keep your OpenAI client; the loop runs on the server.

LLM engines: ContextMemory does not ship or lock to one inference stack. Per tenant you pick any OpenAI-compatible /v1 host — Ollama, vLLM, LM Studio, ExLlamaSharp, OpenAI, Azure-compatible, LiteLLM, custom. Compose ships llama.cpp and vLLM overrides; swap engines per app in Admin → Config → LLM.

How we compare (Mem0 / Zep / Letta / why we are not RAG): docs/compare.md.

What it gives developers

You need…	ContextMemory provides…
Memory that survives turns without rewriting your client	Session markdown wiki + history inject; send only the new message
Memory you can open, edit, audit	Files on disk / Postgres — not opaque embeddings
Shared company/docs knowledge in chat	Global Wiki digests + on-demand `wiki_search` / `wiki_grep` (not classic RAG / embeddings)
Tools without a second orchestrator	Same `/v1`: sandbox + MCP + wiki tools
Safer agents	Skills & guardrail packs, validators, HITL `[CONFIRM:id]`
Cursor / Claude permanent memory fast	MCP wedge: `memory_save` / `memory_search` / `memory_get`
Any LLM per tenant	BYO `/v1` — Ollama, vLLM, LM Studio, ExLlamaSharp, OpenAI, Azure-compatible, custom
Operate without a test client	Admin + Playground
Full control / zero ops	Docker self-host · Kortexio Cloud (`cmk_live_…`)

Capabilities (summary)

Full detail: docs/architecture-and-features.md · Admin: docs/admin-ui.md · HITL: docs/hitl.md.

Area	Highlights
Memory	Session wiki + rolling summary; history budgets; Global Wiki digests/FTS/revisions (`asOf`); no vector RAG
Agentic	Server-side tool loop; sandbox; MCP catalog; artifacts; subagents; validators; HITL; egress policy
Skills	Platform + per-app skills/guardrails (`skill` / `always_on` / `requestable`)
MCP	Outbound wedge (Cursor → CM) · inbound catalog (CM → your MCP servers)
Ops	Admin UI · File or Postgres · Prometheus `/metrics` · Compose (API + Admin + mcp-runtime + sandbox)

More ways to run

The gateway talks OpenAI-compatible /v1 to the engine (and Ollama native /api/chat when you need num_ctx). Change the engine anytime in Admin → Config → LLM or PATCH /admin/apps/{id}/config.

Engine already running (llama-server, vLLM, LM Studio, …) — API image only

docker run --rm -p 5100:8080 \
  -v contextmemory-data:/app/data \
  -e ContextMemory__MasterKey=cm_master_dev_key_change_me \
  -e ContextMemory__Apps__demo-dev__ApiKey=cm_live_dev_key_change_me \
  -e ContextMemory__Apps__demo-dev__LlmBackend=openai-compatible \
  -e ContextMemory__Apps__demo-dev__LlmModel=local-model \
  -e ContextMemory__Apps__demo-dev__LlmEndpoint=http://host.docker.internal:8080 \
  --add-host=host.docker.internal:host-gateway \
  ghcr.io/kortexio/contextmemory:latest

Host-level default for all apps: ContextMemory__LlmEndpoint. Ollama on the host works too (ContextMemory__LlmEndpoint=http://host.docker.internal:11434). Engine flags that matter (llama.cpp --jinja, vLLM tool parser): Engines. Full stack (API + Admin + MCP + sandbox): docs/self-host.md.

Cursor / Claude memory (MCP)

git clone https://github.com/Kortexio/ContextMemory.git
cd ContextMemory/mcp-server && npm install && node print-mcp-config.mjs

Paste into Cursor → Settings → MCP (or ~/.cursor/mcp.json). Same snippet works for Claude Desktop. Details: mcp-server/README.md.

Then, in two separate chats:

Chat	You say	Agent should
A	`Remember: staging DB is postgres-staging-01`	`memory_save`
B (new)	`What is our staging DB?`	`memory_search` + answer

Same flow without Cursor (wiki API, no LLM): ./scripts/aha-demo.sh or .\scripts\aha-demo.ps1.

No GPU, no ops: Kortexio Cloud

	Kortexio Cloud	Self-host (this repo)
Best for	Zero ops	Full control (API + Admin + MCP + sandbox)
Key	`cmk_live_…` (no `X-App-Id`)	`cm_live_…` + `X-App-Id`
Chat body	Identical OpenAI `/v1`	Identical OpenAI `/v1`
LLM	BYO provider in dashboard	BYO engine in Admin / env

Guides: Cloud · Self-host

Chat drop-in

curl -X POST http://localhost:5100/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "X-App-Id: demo-dev" -H "X-User-Id: user-42" -H "X-Session-Id: sess-abc" \
  -H "Authorization: Bearer cm_live_dev_key_change_me" \
  -d '{"model":"local-model","messages":[{"role":"user","content":"Hello"}]}'

Thin header helpers (not full SDKs): @kortexio/contextmemory · kortexio-contextmemory

Documentation & support

Doc	Topic
docs/compare.md	Why it exists · vs Mem0 / Zep / Letta · why we are not RAG
docs/architecture-and-features.md	Wiki, temporal facts, agentic, skills, LLM backends
docs/admin-ui.md	Admin UI map
docs/hitl.md	Human-in-the-loop
docs/api.md	HTTP API
docs/cloud.md · docs/self-host.md	Cloud · Docker / Compose
docs/ops.md	Ops & troubleshooting
docs/README.md	Full docs index

Website: kortexio.io · Email: [email protected]

License

AGPL-3.0 for this open-source core — self-host it freely, including commercially. Need to embed it in a closed-source product without AGPL obligations? Use Kortexio Cloud or a commercial license. See docs/license-and-support.md.