LM Studio with Embeddings

Embeddings make vault search semantic. Without them the MCP uses SQLite full-text search, which matches exact words and phrases. With a local embedding model, searches find related ideas even when the exact words do not appear.

Recommended model: nomic-ai/nomic-embed-text-v1.5 — a good default that works with LM Studio's OpenAI-compatible /v1/embeddings endpoint.

1. Install the plugin

Follow the main install steps first. Make sure the SQLite runtime is installed and the plugin is enabled before continuing.

2. Download an embedding model in LM Studio

lms get nomic-ai/nomic-embed-text-v1.5

Or search for nomic-ai/nomic-embed-text-v1.5 in the LM Studio UI and download from there.

3. Start LM Studio's local server

Load nomic-embed-text-v1.5 as an embedding model.
Start the local server (default URL: http://127.0.0.1:1234/v1).
Verify it is running:

curl http://127.0.0.1:1234/v1/models

Note the exact model identifier in the response — use that value for OBSIDIAN_MCP_EMBEDDING_MODEL if it differs from nomic-embed-text-v1.5.

4. Configure LM Studio `mcp.json`

Open the LM Studio MCP settings and edit mcp.json. Use the full absolute path to mcp-server.cjs and paste the token from Obsidian plugin settings.

{
  "mcpServers": {
    "obsidian-vault": {
      "command": "node",
      "args": [
        "/ABSOLUTE/PATH/TO/Your Vault/.obsidian/plugins/mcp-vault-bridge/mcp-server.cjs"
      ],
      "env": {
        "OBSIDIAN_MCP_BRIDGE_URL": "http://127.0.0.1:27125",
        "OBSIDIAN_MCP_TOKEN": "PASTE_TOKEN_FROM_OBSIDIAN_PLUGIN",
        "OBSIDIAN_MCP_EMBEDDINGS": "on",
        "OBSIDIAN_MCP_EMBEDDING_BASE_URL": "http://127.0.0.1:1234/v1",
        "OBSIDIAN_MCP_EMBEDDING_MODEL": "nomic-embed-text-v1.5"
      }
    }
  }
}

Paths on macOS/Linux: use the full path starting with /. Spaces are fine in JSON — do not escape them with \. If your vault is in Google Drive the real path starts with /Users/USERNAME/Library/CloudStorage/GoogleDrive-ACCOUNT/My Drive/..., not My Drive/....

Reload MCP servers in LM Studio after saving.

5. Build the vault index

Ask LM Studio to run the index refresh tool:

Use the Obsidian vault tool to refresh the index.

The first run reads all included notes, chunks them, stores metadata and full-text data in SQLite, and sends chunks to the embedding endpoint. Embeddings are cached so later refreshes only process changed notes.

After indexing, try:

Search my Obsidian vault for notes related to long-term project risks.

Find notes related to Projects/My Project.md.

Troubleshooting

Symptom	Fix
`args` path starts with `.lmstudio/extensions/...`	The path is relative. Use the full absolute path to `mcp-server.cjs`.
`Cannot find module 'better-sqlite3'`	SQLite runtime is missing. In Obsidian plugin settings: Check runtime → Install SQLite runtime. Requires Node.js 20+.
`NODE_MODULE_VERSION` mismatch for `better-sqlite3.node`	LM Studio is launching the MCP server with a different Node.js major version than the one that installed SQLite. Set `command` in `mcp.json` to the compatible Node path shown in Obsidian's MCP Clients section, or rerun Install SQLite runtime with the Node version you want to use.
`node` command not found	Install Node.js 20+ or set `command` to the absolute path of the `node` executable.
MCP server disconnected in LM Studio	Confirm `mcp-server.cjs` exists at the configured path. Run `npm run plugin:install -- --vault "/path/to/vault"` to reinstall.
MCP server cannot reach Obsidian	Keep Obsidian open with the plugin enabled. Bridge must be running on `127.0.0.1:27125`.
Unauthorized errors	Copy a fresh token from Obsidian plugin settings and update `OBSIDIAN_MCP_TOKEN`.
Embedding errors	Confirm LM Studio's local server is running and `curl http://127.0.0.1:1234/v1/models` lists the embedding model.
Model not found	Replace `nomic-embed-text-v1.5` with the exact identifier shown by LM Studio.
Want to disable embeddings	Remove `OBSIDIAN_MCP_EMBEDDINGS`, `OBSIDIAN_MCP_EMBEDDING_BASE_URL`, and `OBSIDIAN_MCP_EMBEDDING_MODEL`. Full-text search continues to work.

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