Coding agents

Cursor

Give Cursor memory that survives the session. Add the Korely MCP server to one JSON file: no package to install, just your API key in a header.

Connect Korely's MCP server and Cursor can ask Korely for the current facts and the relevant memories before it answers, and save new ones as you work. Korely does the heavy part on its own servers: it reads each memory, writes the facts, closes an older fact when a newer one contradicts it, and keeps both dates of a fact (bi-temporal). Cursor only calls the tools.

Prerequisites

A Korely API key (kor_live_...) without the admin permission. Make it on the dashboard's API keys page, which ticks memories:read and memories:write and leaves admin off. A key from agent signup has admin until you connect it to a dashboard login, and with it a tool can manage the account's projects and close the account; connecting takes admin away, and the key keeps working. The hobby plan is free; Pricing lists its limits.
Cursor installed, with MCP support.

Add the Korely MCP server

Korely's agent memory is a remote MCP server at https://api.korely.ai/agent/mcp, authenticated with your key in a header, no browser login. Cursor reads MCP servers from a JSON file. Open ~/.cursor/mcp.json and add:

{
  "mcpServers": {
    "korely": {
      "url": "https://api.korely.ai/agent/mcp",
      "headers": {
        "Authorization": "Bearer kor_live_..."
      }
    }
  }
}

Replace kor_live_... with your real key. As in the remote example in Cursor's MCP docs, the entry has only url and headers, with no type field. To scope the server to a single project instead of every project, put the same JSON in .cursor/mcp.json in the project root.

Cursor resolves ${env:VAR} inside the url and headers fields, so for a more secure setup keep the key out of the file and read it from the environment:

{
  "mcpServers": {
    "korely": {
      "url": "https://api.korely.ai/agent/mcp",
      "headers": {
        "Authorization": "Bearer ${env:KORELY_API_KEY}"
      }
    }
  }
}

Then export KORELY_API_KEY in the shell that launches Cursor. Either way, manage the server from the Customize page in Cursor; if it does not connect, open the Output panel and pick MCP Logs.

Save every session without asking. In the repository, run korely init --tool cursor (korely-memory 0.1.26 or later): hooks hand Cursor the repository's memory when a session starts and save the session to it as a memory of kind session. Each prompt and each final answer is saved, at most 3,000 characters per message. Before anything leaves your machine, the hook masks private key blocks, credentials in URLs and long random-looking strings. It masks by shape, so a hexadecimal token or a short password typed in a sentence stays as plain text: keep secrets out of what you type. It also writes a local korely MCP server to .cursor/mcp.json in the repository (~/.cursor/mcp.json with --global), replacing a korely entry already there; with --no-mcp it removes that entry and adds none. Without --global, a server you configured in ~/.cursor/mcp.json is kept. The local server has four of the six tools below (no korely_correct_fact or korely_forget_memory). See Connect a coding assistant.

Korely MCP also supports OAuth, so Cursor can sign you in instead of using a key. The Cursor documentation describes OAuth for remote MCP servers. Korely has not tested OAuth with Cursor. See Connect with OAuth.

What Cursor can do

The Korely server offers six memory tools:

Tool	What it does
`korely_get_context`	The recall call: returns the current facts plus the most relevant memories as one block of text, ready to put in a prompt (the context block). It does not call a language model.
`korely_add`	Store a memory. Korely writes facts from it on its servers, each as `(subject, predicate, object)`, and closes an earlier fact, with its end date, when a model decides a new one replaces it.
`korely_search`	Search by meaning over the stored memories, best match first.
`korely_get_facts`	The facts known about an end user, with point-in-time queries: `as_of` (what was true then) and `known_as_of` (what the store knew then).
`korely_correct_fact`	Fix or end one fact by its id. Give a new `subject`, `predicate` or `object` and the old fact is closed and a corrected one is written, both kept in history. With `close=true` the fact is only closed, which is how you forget a fact. Needs a key with the `memories:write` permission.
`korely_forget_memory`	Forget one memory by its id. It drops out of every read and the facts only it stated are closed; with `erase=true` it is removed for good. Needs `memories:write`.

Use it

Korely MCP sends its client short instructions: call korely_get_context before answering, and korely_add once a decision or preference is settled. If Cursor follows them, a session looks like this (an example, not a recording):

You › Remember that this repo deploys to Hetzner, not Render.
      → korely_add("This repo deploys to Hetzner, not Render")

# next session, days later
You › How do we deploy this?
      → korely_get_context("deploy") → "This repo deploys to Hetzner..."
Cursor › This repo deploys to Hetzner (you told me earlier), not Render. ...

Scoping

The four tools korely_get_context, korely_add, korely_search and korely_get_facts accept an optional user_id so one key can serve many end users: a read that names "user-b" never returns a memory written for "user-a". Omit it on a write and the memory belongs to no end user (a key confined to one end user writes to that one). Omit it on a read and the read covers every end user the key can see. korely_add and the three read tools also accept an optional agent_id. korely_correct_fact and korely_forget_memory take the id of a fact or a memory instead, and treat an id from another project (or, for a confined key, from another end user) as not found. The Korely MCP page lists every argument.

Why this is more than a notepad. Korely keeps each memory's text as written and also extracts typed facts with bi-temporal validity from it. When something changes ("this repo now deploys to Hetzner, not Render"), Korely closes the old fact with its end date instead of overwriting it, so korely_get_context returns what's true now, and as_of can still replay what was true before. The Cloud runs on servers in Helsinki; Data and governance says where text is processed.

Korely MCP, the full MCP surface and other clients.
Get context, the call behind korely_get_context.
Memory as a tool, the same pattern when you build the agent loop yourself.