Dev & Engineering persistent-memoryobsidian-vaultknowledge-managementsemantic-searchcodex-cligemini-climcp-server

Obsidian Mind

Persistent, searchable memory for AI coding agents across sessions and repositories.

FollowAgents review · FARS-2.1
Recommended
79/ 100 5-point scale 4.0 / 5
1 2 3 4 5 6
Per-dimension scores and reasoning
1Trust21 / 29 · 3.6/5

The sources describe local models, index isolation, exposed roots, private-tag exclusion, read logging, repository-scoped memories, migration approval, and Git-based update paths in substantial detail. Tests also show rejection of traversal-shaped configuration, while prompts explicitly favor copying over deletion. Author, design influences, and MIT copyright attribution are clear, supporting full source-attribution credit. Deductions apply because ordinary workflows automatically write and reorganize extensive personal and workplace notes; cross-repository sessions can still read the vault directly, and the README concedes that preventing leakage into public PRs relies mainly on an instruction contract rather than enforced access control. The supplied implementation does not fully establish authorization boundaries for Slack, GitHub, or MCP access. Dependency evidence gives versions and fallbacks but no lockfile, audit policy, SBOM, hash pinning, or vulnerability-response evidence.

2Reliability9 / 14 · 3.2/5

The documented architecture, commands, lifecycle, and fallback story are broadly coherent, while supplied tests materially support hygiene scanning, path filtering, missing-directory handling, deadline behavior, and reporting of cleanup failures. Lexical fallback without QMD, CPU fallback, diagnostics, and explicit Node requirements improve dependency availability. Deductions apply because many MCP, migration, classification, command, and cross-client behaviors are assertions without corresponding supplied implementation or tests. Failure-message evidence is concentrated in test helpers and hygiene hints and does not establish consistent actionable errors across installation, external integrations, and all write paths.

3Adaptability16 / 18 · 4.4/5

The material thoroughly addresses personal memory, project work, meetings, incidents, reviews, and cross-repository knowledge, with differentiated support statements for Claude Code, Codex CLI, Gemini CLI, and other clients. Boundaries are unusually explicit: QMD is optional, automatic memory loading is Claude-specific, folder-name identity can collide, affirmative MCP instructions may be ignored, model downloads are substantial, and the Node flag may change. Hook timing, classifications, exclusions, budgets, and degradation rules are precise. Environment-fit points are deducted because complete compatibility across the three primary clients and MCP is not corroborated by the supplied configurations or integration tests, and other clients are expressly only partially supported.

4Convention16 / 18 · 4.4/5

Information architecture, directory responsibilities, template fields, command naming, and daily workflows are documented comprehensively. Clone, ShardMind, QMD, upgrade, migration, dry-run, and approval procedures are concrete. Model sizes, performance costs, repository-name collisions, the experimental Node flag, and client-support differences are candidly documented, and the full MIT text is present. Deductions apply because there is no formal FAQ, some integration examples depend on omitted implementation, and CHANGELOG/version information is referenced but not supplied. Maintenance has a named author, contribution rules, PR-title enforcement, and update paths, but no clear support commitment, release ownership, or broader governance. Unverified publisher identity is treated as unknown rather than adverse.

5Effectiveness12 / 13 · 4.6/5

The intended outputs are directly usable: structured notes, decision records, incident timelines, review briefs, indexes, backlinks, and hygiene warnings all have clear destinations, and tests support actionable wording for part of the hygiene system. Hierarchical loading, injection budgets, local models, keyword fallback, and tiered search costs make the cost-benefit story unusually transparent. Marginal-value credit is reduced because the broad benefits of persistent memory and automatic organization are principally product claims in the README; the supplied evidence lacks representative generated artifacts, comparisons, or static implementation coverage of the core end-to-end workflows needed to establish the claimed advantage over an ordinary Obsidian template plus agent instructions.

6Verifiability5 / 8 · 3.1/5

Some claims trace directly to the license, CI workflows, and named tests. Test comments also connect behavior to concrete failure modes and distinguish successful cleanup, recorded residue, rejected paths, and hygiene states that can return to zero. Deductions apply because most product capabilities are described by a single translated README, while the key MCP, privacy, migration, cross-client, and cost-recording implementations are absent from the supplied evidence, limiting corroboration. The product explicitly labels knowledge as verified, inferred, or unverified and discloses several measurement conditions and failure boundaries, but claims such as the store becoming more reliable as it grows, full cross-client support, and observed behavioral effectiveness are not consistently separated from inference or backed by independent source evidence.

Evidence confidence: Low Reviewed Sep 21, 2026 Reviewed revision af615d100a1d
Before you use it
  • The vault may contain employer-confidential material, client data, meeting records, and performance information. Treat the prompt contract as a soft control and independently inspect file permissions, exposed roots, and generated output before connecting other repositories or opening public PRs.
  • Before enabling Slack, GitHub, MCP, QMD, or reason features, verify actual permissions, inherited authentication, read logs, network behavior, and retention. The supplied implementation does not fully establish these boundaries.
  • Use a separate branch or backup and run dry-run workflows before automatic writes, reorganization, or upgrades. Git and three-way merging provide recovery paths but do not guarantee that every agent-generated content change is easy to reverse.
  • Installation introduces Node, ShardMind, QMD, GitHub Actions, and several local models. Add dependency locking, provenance checks, and vulnerability review, especially for global npm installs and first-use model downloads.
  • Validate complete Codex, Gemini, and cross-repository MCP behavior in the intended environment. This static assessment did not execute the code and does not judge runtime correctness or reproducibility.
Review evidence [1][2][3][4][5][6][7]
See the full review method →

What does this agent do, and when should you use it?

Obsidian Mind is a self-hosted Obsidian vault template that stores projects, people, decisions, incidents, performance evidence, and durable lessons as linked Markdown notes. SessionStart, UserPromptSubmit, PostToolUse, PreCompact, and Stop hooks inject context and validate agent activity for Claude Code, Codex CLI, and Gemini CLI. The repository includes commands, specialized subagents, note templates, Obsidian Bases views, TypeScript hook scripts, and an optional om MCP server for reaching the vault from other code repositories. QMD adds local hybrid semantic retrieval, while installations without it fall back to grep, the Obsidian CLI, and lexical matching. Durable data stays in a user-controlled filesystem and can be versioned with Git, but adopters must work within the vault's folder, frontmatter, and linking conventions.

At session startup, SessionStart reindexes or self-heals QMD and injects a byte-budgeted view of the North Star, active projects, open tasks, recent Git changes, and the vault file listing. UserPromptSubmit classifies each message for decisions, incidents, wins, 1:1s, architecture, people, and project updates, while PostToolUse checks Markdown writes for frontmatter, wikilinks, correct placement, and excessive size. Commands including om-standup, om-dump, om-wrap-up, om-weekly, om-review-brief, om-incident-capture, and om-vault-audit create or update project notes, decision records, incident documents, people profiles, the Brag Doc, review material, and indexes. PreCompact backs up session transcripts under thinking/session-logs/, and Stop runs an end-of-session checklist with concrete vault-hygiene findings. The optional om MCP server exposes search, expand, recall, remember, record_work, reason, and health to sessions in other repositories, applying project identity, scope, confidence, and exposure rules to cross-repository reads and memory writes.

  1. An engineer juggling several codebases wants every new session to recover current goals, active work, blockers, and recent decisions automatically.
  2. A team member recording architectural choices wants decisions, rejected alternatives, people, and project notes connected into an auditable evidence graph.
  3. A developer preparing for performance review wants ongoing wins, competency evidence, 1:1 feedback, incident contributions, and peer PR evidence assembled into review briefs.
  4. An incident responder needs a Slack discussion turned into a timeline, root-cause analysis, participant profiles, and follow-up actions, subject to having the relevant external access.
  5. A developer working across repositories wants any coding session to search a personal vault and write back project- or platform-scoped lessons through the om MCP server.
  6. An existing Obsidian user wants to preview and migrate an older or unrelated vault with om-vault-upgrade while leaving the source vault untouched.

What are this agent's strengths and limitations?

Pros
  • Durable knowledge uses ordinary Markdown, YAML frontmatter, wikilinks, and Git rather than a proprietary hosted database, while remaining directly browsable in Obsidian.
  • The same TypeScript hooks and commands cover Claude Code, Codex CLI, and Gemini CLI; Claude Code additionally receives the fully documented subagent and auto-memory experience.
  • Budgeted, tiered context loading injects summaries and file listings at startup and retrieves details on demand instead of placing the full vault in every context window.
  • The repository supplies an end-to-end path from daily work notes to competency evidence, a Brag Doc, and review briefs rather than offering memory retrieval alone.
  • The om MCP layer supports cross-repository search, graph expansion, work records, and memories with explicit scope, confidence, provenance, and read logging.
Limitations
  • Adoption requires Obsidian 1.12+, Node.js 22+, Git, a supported CLI coding agent, shell access, and a writable local filesystem; this is not a managed service.
  • Claude Code has full support, while Codex CLI and Gemini CLI use the shared hooks and commands through their own conventions; other editor agents only receive AGENTS.md guidance and have varying hook support.
  • QMD is optional but described as materially improving retrieval; its full stack adds roughly 2.25 GB of model downloads and can make semantic queries take several seconds.
  • Cross-repository om MCP use requires an absolute-path registration plus specific instructions in every consuming repository; server registration alone may result in no vault calls.
  • Users must maintain the North Star, classifications, frontmatter, links, project identities, and exposure boundaries; mistakes can produce retrieval gaps, same-name project collisions, or unintended exposure.
  • Hook execution relies on Node's --experimental-strip-types flag, so a future removal or rename would require one-line changes across the Claude, Codex, and Gemini hook configurations.

How do you install or deploy this agent?

Install Obsidian 1.12+, Node.js 22+ LTS, Git, and one of Claude Code, Codex CLI, or Gemini CLI. The recommended installation is:

npm install -g shardmind
mkdir my-vault && cd my-vault
shardmind install github:breferrari/obsidian-mind

The wizard collects identity, organization, vault purpose, included agents, and the QMD choice; it also initializes Git and personalizes brain/North Star.md. A direct installation is also documented:

git clone https://github.com/breferrari/obsidian-mind.git

Open the resulting directory as an Obsidian vault, enable Obsidian CLI under Settings → General, and run claude, codex, or gemini from that directory. To add the recommended local semantic search layer, run:

npm install -g @tobilu/qmd
node --experimental-strip-types .scripts/qmd-bootstrap.ts

QMD downloads three local models of roughly 328 MB, 1.28 GB, and 640 MB on first use; it is optional rather than a core prerequisite.

How do you use this agent?

Start the chosen coding agent from the vault directory. Run om-standup in the morning—written as /om-standup in Claude Code—to load goals, active projects, tasks, and recent changes. After a meeting or work session, pass free-form notes to om-dump so the agent can route people, decisions, wins, and project updates into the appropriate files. Say “wrap up” or run om-wrap-up at the end of the day to validate notes, refresh indexes, check links, and identify uncaptured wins; use om-weekly and om-vault-audit for periodic synthesis and maintenance. Fill in brain/North Star.md before regular use, then adapt org/, perf/competencies/, and CLAUDE.md to the organization. To reach the vault from other repositories, register the MCP server once:

claude mcp add --scope user om node "/absolute/path/to/your-vault/.claude/scripts/om-mcp.mjs"

Then add concrete consultation triggers to each consuming repository's CLAUDE.md. The documentation reports that registering the server without repository-side instructions does not reliably cause sessions to consult it.

How does this agent compare with similar options?

Compared with a direct git clone, ShardMind adds a personalization wizard, optional modules, and three-way-merge upgrades. With all defaults, its installed vault is documented as byte-equivalent to the clone, and the vault still works after removing .shardmind/ and shard-values.yaml. Compared with grep or Obsidian CLI retrieval alone, QMD adds local vector search, query expansion, and reranking, which can recover semantically related notes with different wording at the cost of model downloads, latency, and local compute. Among supported coding agents, Claude Code receives full support; Codex CLI and Gemini CLI share the hooks and commands, while Cursor, Windsurf, GitHub Copilot, and JetBrains AI are only documented as able to read AGENTS.md, with hook support varying by product.

FAQ

Is QMD required?
No. Without QMD, the vault falls back to grep, Obsidian CLI, and lexical matching. Notes remain available, but semantic recall and ranking are weaker.
Does search require an API key or per-query fees?
QMD runs its three models locally, requires no API key or per-query charge, and can work offline after setup. The om MCP reason operation is different: it launches a second Claude session using the machine's existing Claude CLI authentication and default model.
Does every session receive the entire vault?
No. SessionStart injects budgeted excerpts, tasks, Git context, and a file listing. Full notes are read only when needed, usually after targeted QMD retrieval.
How can I restrict what other repositories read?
The default exposed content follows user_content_roots in vault-manifest.json. Set mcp_exposed_roots when the vault contains material that should not be shared; notes tagged private are never served by om MCP, and cross-repository reads are logged with the calling repository.
What happens when two repositories have the same folder name?
om MCP normally uses the folder name as repository identity, so two folders named api share an identity and memories. Add a distinct .om-project file at each repository root and use health to confirm the resolved identity.

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