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setup

Install Memoria and configure MCP for AI tools (Kiro, Cursor, Claude Code, Codex, Gemini CLI). Decision tree for Cloud vs self-hosted mode, database, embedding provider. Use when helping users set up Memoria.

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matrixorigin/Memoria
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25 mars 2026 à 10:53
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SKILL.md
Instructions source · Aperçu en lecture seule
name
setup
description
Install Memoria and configure MCP for AI tools (Kiro, Cursor, Claude Code, Codex, Gemini CLI). Decision tree for Cloud vs self-hosted mode, database, embedding provider. Use when helping users set up Memoria.
## Decision Tree Follow these steps in order. Steps marked "Self-Hosted only" can be skipped for Memoria Cloud users. ### Step 1: Memoria Cloud or Self-Hosted? Ask: "Use Memoria Cloud, or run your own instance?" - **Memoria Cloud (recommended)** → sign up at [thememoria.ai](https://thememoria.ai/auth), get API URL + token, then proceed to Step 2 - **Self-hosted** → proceed to Step 2 ### Step 2: Which AI tool? Ask: "Which AI tool are you using — Kiro, Cursor, Claude Code, Codex, or Gemini CLI?" The `--tool` flag value and config files generated per tool: | Tool | `--tool` value | Config files | |------|---------------|--------------| | Kiro | `kiro` | `.kiro/settings/mcp.json` + `.kiro/steering/memory.md` | | Cursor | `cursor` | `.cursor/mcp.json` + `.cursor/rules/memory.mdc` | | Claude Code | `claude` | `.mcp.json` + `CLAUDE.md` | | Codex | `codex` | `~/.codex/config.toml` + `AGENTS.md` | | Gemini CLI | `gemini` | `.gemini/settings.json` + `GEMINI.md` | ### Step 3: Database (Self-Hosted only) Skip this step if user chose Memoria Cloud in Step 1. Ask: "Do you have a MatrixOne database running?" - Already have one → get connection URL (format: `mysql+pymysql://<user>:<pass>@<host>:<port>/<db>`) - No → run `docker compose up -d` in the Memoria repo root (wait 30-60s for first start) ### Step 4: Embedding provider (Self-Hosted only) Skip this step if user chose Memoria Cloud in Step 1. ⚠️ **Hard to reverse.** Embedding dimension is locked into schema on first startup. Ask: "Do you have an OpenAI-compatible embedding endpoint?" - Yes → collect: base URL, API key, model, dimension - No → suggest SiliconFlow (free tier) or Ollama. Local embedding requires `--features local-embedding` build. ### Step 5: Install Memoria CLI The `memoria` binary is required for all modes — it serves as the MCP bridge between the AI tool and the Memoria server. One-line install (recommended): ```bash curl -sSL https://raw.githubusercontent.com/matrixorigin/Memoria/main/scripts/install.sh | bash ``` Or download manually from [GitHub Releases](https://github.com/matrixorigin/Memoria/releases). Platform-specific manual install: ```bash # Linux x86_64 curl -LO https://github.com/matrixorigin/Memoria/releases/latest/download/memoria-x86_64-unknown-linux-musl.tar.gz tar xzf memoria-x86_64-unknown-linux-musl.tar.gz && sudo mv memoria /usr/local/bin/ # macOS Apple Silicon curl -LO https://github.com/matrixorigin/Memoria/releases/latest/download/memoria-aarch64-apple-darwin.tar.gz tar xzf memoria-aarch64-apple-darwin.tar.gz && sudo mv memoria /usr/local/bin/ # From source (required for local embedding) cd Memoria/memoria && cargo build --release -p memoria-cli # With local embedding: cargo build --release -p memoria-cli --features local-embedding sudo cp target/release/memoria /usr/local/bin/ ``` Verify: `memoria --version` ### Step 6: Configure ### Memoria Cloud (Remote Mode) Sign up at [thememoria.ai](https://thememoria.ai/auth) — after login you will receive the API URL and token. ```bash cd <user-project> memoria init --tool <tool> --api-url '<API URL from thememoria.ai>' --token '<your token>' ``` Replace `<tool>` with the value from Step 2 (e.g., `kiro`, `cursor`, `claude`, `codex`, `gemini`). ### Self-Hosted: Local Docker ```bash docker compose up -d # Start MatrixOne docker ps --filter name=matrixone # Verify (wait 30-60s) cd <user-project> memoria init --tool <tool> # + embedding flags below ``` ### Self-Hosted: Existing DB ```bash cd <user-project> memoria init --tool <tool> --db-url 'mysql+pymysql://<user>:<pass>@<host>:<port>/<db>' ``` ### Embedding Flags (Self-Hosted only) ```bash # Local (default, no flags) memoria init --tool <tool> # OpenAI-compatible memoria init --tool <tool> \ --embedding-provider openai \ --embedding-base-url https://api.siliconflow.cn/v1 \ --embedding-api-key sk-... \ --embedding-model BAAI/bge-m3 \ --embedding-dim 1024 ``` ### Step 7: Verify After running `memoria init`, tell user to: 1. Restart their AI tool 2. Ask the AI: *"Do you have memory tools available?"* 3. Or run: `memoria status` Expected: `memory_retrieve("test")` → "No relevant memories found". ## Post-Setup ```bash memoria rules --force # After upgrading Memoria binary, re-sync steering rules ``` ## MCP Server Modes (Reference) These are the underlying commands that `memoria init` configures. Users normally don't need to run them directly. ```bash # Embedded mode (direct DB connection, self-hosted) memoria mcp --db-url "mysql+pymysql://root:111@localhost:6001/memoria" --user alice # Remote mode (proxy to Memoria API server, Cloud or self-hosted API) memoria mcp --api-url "<API URL>" --token "<token>" # SSE transport (alternative to default stdio) memoria mcp --transport sse ``` ## Troubleshooting | Problem | Fix | |---------|-----| | MatrixOne won't start | `docker logs memoria-matrixone` | | Port 6001 in use | Change `MO_PORT` in `.env` | | Can't connect to DB | Wait 30-60s on first start | | Docker permission denied | `sudo usermod -aG docker $USER && newgrp docker` | | Docker not available | Use [Memoria Cloud](https://thememoria.ai/auth) instead (no Docker needed) | | First query slow | Normal with local embedding (~3-5s). Use `openai` provider for faster response | | `local-embedding` not compiled | Use OpenAI-compatible service, or build from source with `--features local-embedding` | | AI tool doesn't see memory tools | 1. Run `which memoria` to verify CLI installed 2. Restart AI tool 3. Test MCP server directly |
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