Glassmind

Local-first retrieval for Obsidian-like markdown knowledge bases and AI workflows.

Glassmind turns a folder of markdown notes into searchable local memory for humans, agents, and local model workflows.

It works well with Obsidian vaults, but Obsidian is not required. A plain directory of .md files is enough. Your notes stay local. Markdown stays canonical. The SQLite database is a rebuildable cache.

Current Status

Glassmind now runs as a Rust CLI MVP.

It can:

• scan a markdown vault
• parse headings, paragraphs, lists, code blocks, tags, and wikilinks
• split notes into heading-based retrieval chunks
• store metadata and chunks in SQLite
• index chunks with SQLite FTS5 keyword search
• generate local deterministic embeddings
• score results with keyword, semantic, recency, tag, and wikilink signals
• build context bundles with token budgets
• expose a small localhost HTTP API
• expose MCP-style command output
• write agent-owned memories, tasks, and decisions under .agent/
• skip unchanged files with content hashes
• audit retrievals for debugging

Some pieces are still intentionally lightweight:

• the Ollama backend has the right interface, but does not call Ollama over HTTP yet
• vectors are stored as JSON in SQLite, not native sqlite-vec yet
• the HTTP server is a small standard-library server, not Axum yet
• MCP support is command-shaped, not a full MCP protocol server yet
• watch mode is simple polling

The core local retrieval flow is in place and usable for testing.

What Glassmind Is

Glassmind is not:

• a chatbot
• an Obsidian plugin
• an autonomous agent
• a replacement for Obsidian
• a cloud memory service

Glassmind is a memory and retrieval layer.

Claude / Codex / local model / your tooling
                |
           Glassmind
                |
       your markdown vault

The goal is simple:

Given this task, what context from my vault actually matters?

Quick Start

Build it:

cargo build

Index the current repo:

cargo run -- index --embeddings

Search:

cargo run -- search "local memory" --debug-scores

Build a context bundle:

cargo run -- context "continue glassmind" --budget 3000

Use a personal Obsidian vault:

cargo run -- --vault "E:\notes\Brain" index --embeddings
cargo run -- --vault "E:\notes\Brain" search "project ideas" --debug-scores
cargo run -- --vault "E:\notes\Brain" context "what was I thinking about local agents?"

If your vault path has spaces, keep the quotes.

Configuration

Glassmind reads glassmind.toml by default.

Useful defaults:

[vault]
path = "."

[database]
path = ".agent/cache/glassmind.sqlite3"

[index]
include_agent_dir = true
ignore_dirs = [".git", ".obsidian", ".trash", ".agent/cache"]
chunk_target_tokens = 500
chunk_overlap_tokens = 80

[embeddings]
backend = "ollama"
model = "nomic-embed-text"
url = "http://localhost:11434"

[server]
host = "127.0.0.1"
port = 7331

The database path is inside .agent/cache so it stays out of Git and can be rebuilt.

CLI Commands

Initialize config and agent workspace:

cargo run -- init

Index once:

cargo run -- index

Index and generate missing embeddings:

cargo run -- index --embeddings

Poll and reindex every five seconds:

cargo run -- index --watch

Search:

cargo run -- search "obsidian rag memory"

Search with score breakdown:

cargo run -- search "obsidian rag memory" --debug-scores

JSON search:

cargo run -- search "obsidian rag memory" --output json

Context bundle:

cargo run -- context "help me continue the Glassmind project" --budget 6000

Stats:

cargo run -- stats

Agent Memory

Glassmind owns .agent/.

.agent/
  memories/
  summaries/
  tasks/
  decisions/
  logs/
  cache/

Capture generated memory:

cargo run -- capture memory --project Glassmind --text "Markdown remains canonical."
cargo run -- capture task --project Glassmind --text "Wire real Ollama HTTP embeddings."
cargo run -- capture decision --project Glassmind --text "SQLite is rebuildable cache."

Those files are markdown and are indexed on the next run.

HTTP API

Start the local server:

cargo run -- serve

Default bind:

127.0.0.1:7331

Endpoints:

• GET /health
• GET /stats
• POST /search
• POST /context
• GET /notes/{path}

Example:

curl http://127.0.0.1:7331/health

MCP-Style Commands

List tools:

cargo run -- mcp tools

Search:

cargo run -- mcp search "local memory"

Context:

cargo run -- mcp context "continue glassmind"

Read:

cargo run -- mcp read "README.md"

Architecture

Markdown vault
  -> scanner
  -> parser
  -> heading chunker
  -> SQLite metadata cache
  -> FTS keyword index
  -> embedding cache
  -> hybrid retriever
  -> CLI / HTTP / MCP-style tools

Core principle:

markdown = source of truth
sqlite = rebuildable cache
embeddings = derived retrieval data
.agent/ = Glassmind-owned workspace

Documentation

• Design Document
• FAQ
• HUH? Beginners Guide
• Technical Explainer

Security And Privacy

By default:

• runs locally
• binds HTTP to localhost
• keeps notes on disk
• avoids modifying normal user notes
• writes generated data under .agent/
• stores indexes under .agent/cache
• does not require cloud APIs
• has no telemetry

Tech Stack

Current:

• Rust
• SQLite
• SQLite FTS5
• rusqlite
• clap
• serde
• pulldown-cmark
• tracing

Planned improvements:

• real Ollama HTTP embeddings
• native sqlite-vec
• Axum HTTP server
• full MCP transport
• filesystem watcher

Legal

Glassmind is an independent project and is not affiliated with or endorsed by Obsidian.