Skip to main content
Glama

@kireo/mcp-server

Long-term memory for any MCP-compatible AI tool (Claude Code, Cursor, Windsurf, Cline, Zed, Continue …).

npm version

What is Kireo memory MCP?

Kireo memory MCP is a Model Context Protocol server that gives Claude Code, Cursor, Cline, Windsurf and any other MCP client long-term memory. Save a decision once; recall it in any later session, on any machine. Hybrid semantic + keyword search over LanceDB, eight MCP tools, plus local code indexing. Free beta — an API key is all you need.

How do I install Kireo memory MCP?

One line for Claude Code, one JSON block everywhere else. Both need a free key from https://app.kireo.app/app/api-keys (ki_sk_…).

# Claude Code — add --scope user to get it in every project
claude mcp add kireo --scope user --env KIREO_API_KEY=ki_sk_xxx -- npx -y --package=@kireo/mcp-server kireo-mcp

Every other client takes the same server entry; only the file it goes in differs:

{
  "mcpServers": {
    "kireo": {
      "command": "npx",
      "args": ["-y", "--package=@kireo/mcp-server", "kireo-mcp"],
      "env": { "KIREO_API_KEY": "ki_sk_xxx" }
    }
  }
}

Client

Where that block goes

Claude Code

.mcp.json in the project root (or use the claude mcp add line above)

Cursor

~/.cursor/mcp.json, or <workspace>/.cursor/mcp.json for one repo

Cline

MCP Servers → Configure MCP Servers (cline_mcp_settings.json)

Claude Desktop

claude_desktop_config.json (Settings → Developer → Edit Config)

Windsurf

~/.codeium/windsurf/mcp_config.json

Zed / Continue / any MCP host

Whatever that host calls its MCP server list — same three fields

Restart the client afterwards. Node.js ≥ 18 must be on PATH for npx.

Which tools does it expose?

Eight, over MCP stdio: memory_save, memory_search, memory_recall, memory_get, memory_update, memory_delete, memory_list_namespaces, memory_health. Every client sees the same set. Call memory_health first to confirm the key works.

Does it bloat my prompt?

No — memory is pulled, not pushed. Nothing is injected into the system prompt. The agent calls memory_search only when it decides prior context is worth retrieving, and gets back a bounded ranked set (default 10 hits, hard cap 50), so tokens are spent per-query rather than per-turn.

How is it different from a CLAUDE.md / .cursorrules file?

A rules file is static text re-read in full every session and shared by nothing. Kireo memory MCP is queried on demand, is written by the agent as work happens, is searchable semantically, and is shared across projects, sessions and machines through namespaces.

Can it index my codebase?

Yes. npx -y -p @kireo/mcp-server kireo index ./ --repo my-app extracts functions/classes/methods into a code-<repo> namespace that memory_search can reach. Indexing is incremental — re-runs only send changed files, and the server dedupes identical symbols, so retrying is safe.

Is my code uploaded?

No. Only the content explicitly passed to memory_save (and, if you run kireo index, the symbols it extracts) leaves your machine. Set KIREO_TELEMETRY=0 to also drop the X-Device-Id header.

What does it cost?

Free beta. Sign up at https://app.kireo.app, create a key, done — no card.

Related MCP server: mindcore-memory-mcp

Quickstart

  1. Get an API key at https://app.kireo.app/app/api-keys (ki_sk_…).

  2. Add this MCP server to your host. Claude Code — run:

claude mcp add kireo --scope user --env KIREO_API_KEY=ki_sk_xxx -- npx -y --package=@kireo/mcp-server kireo-mcp

Two details in that line are load-bearing, both verified against claude 2.1.220 and npm 11 on 2026-08-03:

  • --package=@kireo/mcp-server kireo-mcp, not @kireo/mcp-server. This package ships two binaries (kireo, kireo-mcp), neither named after the package, so npx -y @kireo/mcp-server cannot pick one and fails with could not determine executable to run.

  • --package=, not the short -p. A bare -p after -- gets swallowed by the claude mcp add option parser, which then rejects its own flag: claude mcp add kireo --env … -- npx -y -p @kireo/mcp-server kireo-mcp errors with unknown option '--env'. The long form parses cleanly.

Drop --scope user if you only want it in the current project. Alternatively, check a project-scoped .mcp.json into your repo root with the same shape (inside JSON args the short -p is fine — it goes straight to npx and never reaches the claude parser):

// .mcp.json (project root)
{
  "mcpServers": {
    "kireo": {
      "command": "npx",
      "args": ["-y", "--package=@kireo/mcp-server", "kireo-mcp"],
      "env": { "KIREO_API_KEY": "ki_sk_xxx" }
    }
  }
}
  1. Restart the host. You now have 8 tools available to the AI:

Tool

Purpose

memory_save

Persist a long-term memory

memory_search

Hybrid semantic + keyword search

memory_recall

Replay recent/important memories

memory_get

Fetch by id

memory_update

Patch fields

memory_delete

Soft/hard delete

memory_list_namespaces

Enumerate namespaces

memory_health

Probe service

Configuration

Sources are merged in order: CLI args > env > ~/.kireo/config.json.

ENV / CLI

Default

Description

KIREO_API_KEY / --api-key

required

Bearer token (ki_sk_…).

KIREO_API_URL / --api-url

https://api.kireo.app

Override for self-host.

KIREO_REQUEST_TIMEOUT_MS / --timeout

60000

Per-request timeout in ms, max 300000 (env alias: KIREO_TIMEOUT_MS).

KIREO_RETRY_MAX_ATTEMPTS

3

5xx/429 retries (alias: KIREO_RETRY_MAX).

KIREO_RETRY_BASE_MS

200

Exponential backoff base.

KIREO_TELEMETRY

1

Set to 0 to disable device-id header.

KIREO_LOG_LEVEL

info

debug / info / warn / error / silent.

KIREO_PROXY_URL

none

HTTP(S) proxy.

KIREO_ACCEPT_LANGUAGE

en

Locale for error hints.

Logs land in ~/.kireo/logs/ on all platforms (macOS, Linux, Windows).

Indexing local code

Index a repository's symbols (functions / classes / methods) into a code-<repo> namespace so the AI can recall them via memory_search:

export KIREO_API_KEY=ki_sk_xxx
npx -y -p @kireo/mcp-server kireo index ./ --repo my-app

Indexing is incremental — only changed files are re-sent on subsequent runs.

Flag

Default

Description

--repo <name>

directory basename

Repo name → code-<name> namespace.

--batch-size <n>

100

Symbols per upload batch (1..100). Lower it if a batch times out.

--timeout <ms>

60000

Per-request timeout (max 300000).

--api-key / --api-url / --namespace / --log-level / --no-telemetry

Same as the config table above; CLI flags override env.

Run kireo --help for the full usage text. --help and --version never touch the network or the filesystem and don't require an API key. If a batch upload times out, re-running the same command is safe: the server dedupes identical symbols, so retries won't create duplicates.

Host setup

Privacy

Set KIREO_TELEMETRY=0 to drop the X-Device-Id header. We never read your code; only the explicit content you pass to memory_save reaches the API.

Troubleshooting

  • AUTH_INVALID_KEY → rotate your key at https://app.kireo.app/app/api-keys.

  • QUOTA_EXCEEDED → upgrade or wait for next billing cycle.

  • Tools missing in your host → run npx @modelcontextprotocol/inspector node $(npm root -g)/@kireo/mcp-server/bin/kireo-mcp.cjs to verify locally.

License

MIT

Install Server
A
license - permissive license
A
quality
A
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

Related MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    A self-hosted MCP server that provides AI assistants with a shared, persistent SQLite-backed memory for storing and retrieving project context, decisions, and discoveries. It enables cross-session continuity and team-wide knowledge sharing to keep AI coding tools aligned and informed.
    3
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    A production-grade long-term memory MCP server that enables AI agents to persist and recall memories across sessions with importance weighting, confidence calibration, and efficient context window management.
    9
    1
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A lightweight MCP server that provides long-term memory for LLMs by storing and retrieving important facts, decisions, and preferences through smart semantic search and automatic organization.
    10
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    A long-term memory MCP server for AI agents that stores memories (facts, decisions, etc.) in a single SQLite database with hybrid search and full edit history, ensuring consistency across sessions.
    24
    MIT

View all related MCP servers

Related MCP Connectors

  • Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.

  • Cloud-hosted MCP server for durable AI memory

  • Shared long-term memory vault for AI agents with 20 MCP tools.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/wang1051992187/kireo-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server