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  3. Kortexio Memory
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Kortexio Memory

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Hosted ambient memory for AI agents. Retrieve context and save notes via MCP tools with OAuth.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "kortexio-memory": {
      "command": "npx",
      "args": [
        "-y",
        "kortexio-memory"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Documentation Overview

Kortexio ContextMemory β€” Memory you can open as a wiki

Get Cloud key Β· Self-host Β· Docs Β· Demo

License: AGPL-3.0 .NET 9 Docker GHCR Docker CI Tests GitHub commit activity

Your agent forgets. Fix that with memory you can open like a wiki.

One OpenAI-compatible /v1 URL: wiki memory, agentic tool loop, skills/guardrails, MCP, sandbox, and HITL β€” self-hosted or Cloud. Not a vector black box. Not classic RAG inject.


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:

  1. Authenticates the tenant and attaches session wiki + history
  2. Runs an agentic tool loop when tools are enabled (wiki search, sandbox, MCP, …)
  3. Applies skills, guardrails, validators, and optional HITL before destructive actions
  4. Returns a standard OpenAI-shaped chat.completions response (streaming supported)
Code
Your client (OpenAI SDK / Cursor MCP / curl)
        β”‚
        β–Ό  POST /v1/chat/completions
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  ContextMemory (.NET 9)                    β”‚
β”‚  Auth Β· session wiki Β· Global Wiki tool    β”‚
β”‚  Agentic loop Β· skills Β· guardrails Β· HITL β”‚
β”‚  LLM backend (per app, OpenAI-compatible)  β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
        β–Ό                  β–Ό
 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.

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 clientSession markdown wiki + history inject; send only the new message
Memory you can open, edit, auditFiles on disk / Postgres β€” not opaque embeddings
Shared company/docs knowledge in chatGlobal Wiki digests + on-demand wiki_search / wiki_grep (not classic RAG / embeddings)
Point-in-time factsTemporal revisions (asOf / supersede) on Global Wiki
Tools without a second orchestratorSame /v1: sandbox + MCP integrations + wiki tools
Safer agentsSkills & guardrail packs, validators, confirmation keywords, HITL [CONFIRM:id]
Cursor / Claude permanent memory fastMCP wedge: memory_save / memory_search / memory_get (+ wiki_search, session_recall)
Any LLM per tenantOllama, vLLM, LM Studio, OpenAI, Azure-compatible /v1, custom
Operate without writing a test clientAdmin + Playground (timeline, todos, artifacts, HITL)
Full control on your infraDocker/Compose self-host (API + Admin + mcp-runtime + sandbox)
Zero opsKortexio Cloud (cmk_live_…)

Capabilities (full surface)

Memory

  • Session wiki β€” markdown pages, index, execution log; compaction; update every N turns; optional dedicated maintainer model; rolling summary in the system prompt
  • History β€” last N messages (per-app budget); mid-turn compaction archives long transcripts as artifacts when over MaxContextTokens
  • Persona & rules β€” basePersona, businessRules, formatRules, wikiSchema per app
  • Global Wiki β€” app-scoped docs; ingest/batch APIs; digests; FTS; tools wiki_search / wiki_grep; revisions / audit / asOf
  • No vector RAG β€” discovery is digests + lexical/FTS + tools (Cursor-style), not embeddings
  • Web search (optional) β€” enrich turns; can persist into wiki

Agentic harness (server-side)

When agentic tools are enabled, the gateway runs a tool loop:

  • Iterations / timeout β€” max steps, loop timeout, partial answer on timeout; mid-turn compaction phase
  • Built-in tools β€” wiki_search, wiki_grep; sandbox shell_execute / python_execute / node_execute / container_execute (self-hosted or ACA); discovery helpers (artifact_*, skill_*, rule_*, tool_describe, session_log_search, delegate_task, todo_write)
  • Lazy tool schemas β€” MCP and built-ins listed with short/open schemas; tool_describe for full args
  • Artifacts β€” long outputs (and all sandbox runs) stored per session; loop keeps a short preview + artifactId
  • Subagents β€” delegate_task (depth 1, isolated child session)
  • MCP tools β€” per-app catalog (server__tool), allow/deny, max tools per turn, OAuth/credentials
  • Validation modes β€” deterministic Β· hybrid Β· llm-judge
  • Hooks β€” PreToolUse / PostToolUse guardrail kinds
  • HITL β€” pause before destructive tools; [CONFIRM:id] / cancel; checkpoint in session log
  • Progress β€” context_memory.agentic phases (incl. Compacting / Subagent*) + context_memory.discovery counters
  • Prompt profiles β€” auto / ollama / openai / claude / qwen / composer
  • Network egress policy β€” restricted/allowed + host allowlists

Skills & guardrails

  • Platform catalog β€” shared skills/guardrails (Admin β†’ Skills); import .skill.json / .guardrail.json
  • Activation β€” skill | always_on | requestable (rules loaded via rule_search / rule_read)
  • Per-app policies β€” additive inventory on top of platform defaults
  • Seeded examples include anti-hallucination, tool-calling discipline, wiki-first-for-docs, privacy/secrets, transparent failures, and more
  • Guardrail kinds include URL fetch, sandbox claims, tool-failure disclosure, blocked patterns, pre/post tool-use hooks

MCP (two directions)

DirectionRole
Outbound wedgeCursor/Claude β†’ ContextMemory (mcp-server/) for memory tools
Inbound catalogContextMemory agent β†’ your MCP servers (HTTP/stdio via mcp-runtime, OAuth, catalog rebuild)

Admin console

Blazor Admin (:5200, Master Key auth) β€” operators configure tenants without touching JSON by hand:

AreaWhat you configure / do
DashboardApps, requests, wiki/web-search stats
New app / credentialsRegister tenant, mint/rotate cm_live_…
PlaygroundChat Lab: agentic timeline (Compacting/Subagent), Todos, Artifacts, wiki refs, HITL
LLMBackend, model, endpoint, API key, history, streaming, think
Memory & wikiSession budgets, compaction, maintainer model, Global Wiki on/off + char budget
Web searchProvider, mode, persist-to-wiki
Rate limitsRPM/TPM (+ agentic weight)
Persona & rulesPersona, business/format rules, wiki schema
AgenticFull gateway knobs: tools, MCP, sandbox, validators, HITL, egress
Skills & policiesPlatform + per-app skills/guardrails
SettingsAPI base URL, Master Key, health

ContextMemory Admin dashboard

LLM backend picker Β  Agentic gateway config

Admin Playground Β  Skills and guardrails

Guide: docs/admin-ui.md Β· HITL: docs/hitl.md

Self-host stack

Docker Compose brings up a full local platform:

ServiceRole
API (:5100)Gateway /v1, admin APIs, metrics
Admin (:5200)Operator UI
mcp-runtimeStdio/HTTP MCP sidecar
sandbox-runtimeIsolated shell/python/node execution

Persistence: File (single-node) or Postgres (HA + FTS). Images: ghcr.io/kortexio/contextmemory Β· ghcr.io/kortexio/contextmemory-admin.

Observability

Prometheus /metrics Β· OpenTelemetry (Aspire) Β· per-app telemetry in Admin.


Quickstart (5 minutes)

1. Start the gateway

Default demo points at Ollama on the host. Swap the backend anytime in Admin β†’ Config β†’ LLM or PATCH /admin/apps/{id}/config.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Kortexio Memory

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "kortexio-memory": { "command": "npx", "args": ["-y", "Kortexio Memory"] } }

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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