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OpenCode

Give OpenCode memory that survives the session. Add the Korely MCP server to one config file, no OAuth dance, no package to install, just your API key in a header.

Connect Korely's MCP server and, before answering, OpenCode can pull the active typed facts and relevant memories it has stored, and write new ones as it learns. The intelligence, entity and typed-fact extraction, contradiction resolution, bi-temporal validity, runs server-side. OpenCode just calls the tools.

Prerequisites

  • A Korely API key (kor_live_...). The hobby tier is free.
  • OpenCode installed (opencode --version).

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. OpenCode configures MCP servers in opencode.json, so add the server under mcp with type: "remote" and a static bearer header: 

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "korely": {
      "type": "remote",
      "url": "https://api.korely.ai/agent/mcp",
      "enabled": true,
      "headers": {
        "Authorization": "Bearer kor_live_..."
      }
    }
  }
}

Put this in your global config at ~/.config/opencode/opencode.json, or in a project-local opencode.json at the repo root. Replace kor_live_... with the real key from agent signup. The "type": "remote" transport is Streamable HTTP, matching Korely's agent endpoint. JSONC comments are supported if you prefer to annotate the block.

Restart OpenCode and the korely server connects automatically. With a valid key the server accepts the header, so OpenCode gets no 401 and starts no OAuth flow. If you see an OAuth prompt, check that the key is correct and not revoked. You can also add "oauth": false to the entry to turn OAuth detection off.

What OpenCode can do

Once connected, OpenCode has four memory tools:

ToolWhat it does
korely_get_contextThe recall path: assembles the active typed facts plus the most relevant memories into a prompt-ready block. Pure retrieval: the query is embedded once for the vector search, and no generative model runs on the read path.
korely_addStore a memory. Typed (subject, predicate, object) facts are extracted server-side, and a model judge closes the earlier fact, with its end date, when it decides a new one replaces it.
korely_searchSemantic search over stored memories, ranked.
korely_get_factsThe typed bi-temporal facts known about a user, with point-in-time queries: as_of (what was true then) and known_as_of (what the store knew then).

Use it

Now OpenCode reaches for memory on its own. Tell it something durable and it calls korely_add; ask it something personal and it calls korely_get_context first: 

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..."
OpenCode › This repo deploys to Hetzner (you told me earlier), not Render. ...

Scoping

Every tool accepts 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.

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"), the judge 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. EU-hosted.

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