How do I use vault-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@vault-mcp search for notes about connection pooling" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

vault-mcp

by Lincyaw

Overview Schema Related Servers Score Discussions

Python

Local

vault-mcp

Markdown + SQLite knowledge store with bidirectional [[wikilinks]], exposed as an MCP server. Designed for AI agents to maintain an interconnected knowledge base.

Installation

uvx vault-mcp                           # run directly without install
pip install vault-mcp                   # core (keyword search only)
pip install "vault-mcp[semantic]"       # + embedding-based semantic search

Related MCP server: brainforge-mcp

Running the MCP Server

# Start with default settings (vault in ./vault)
vault-mcp

# Custom vault directory
VAULT_DIR=/path/to/notes vault-mcp

# With semantic search enabled
VAULT_DIR=./vault VAULT_EMBEDDING_MODEL=jinaai/jina-embeddings-v5-text-nano vault-mcp

Environment Variables

Variable	Default	Description
`VAULT_DIR`	`./vault`	Root directory for markdown files
`VAULT_EMBEDDING_MODEL`	(none)	Sentence-transformers model name. Enables semantic search when set

Client Configuration

Claude Code

claude mcp add vault -- vault-mcp

Or .mcp.json:

{
  "mcpServers": {
    "vault": {
      "type": "stdio",
      "command": "vault-mcp",
      "env": { "VAULT_DIR": "./vault" }
    }
  }
}

Cursor / Windsurf / Other MCP Clients

Add to your MCP settings:

{
  "vault": {
    "command": "vault-mcp",
    "env": { "VAULT_DIR": "./vault" }
  }
}

Python Library (no MCP)

from vault_mcp import MarkdownVault, create_vault_tools

vault = MarkdownVault("./my-vault")
vault.write("skill/debugging", {"type": "skill", "confidence": "pattern"}, "# Debugging\n\n...")

# Or get all 11 tools as a dict of callables
tools = create_vault_tools(vault)
result = tools["vault_search"](query="debugging", mode="keyword")

Note Format

Each note is a .md file with YAML frontmatter, organized in type-based folders:

vault/
  skill/
    timeout-diagnosis.md
  concept/
    connection-pooling.md
  episodic/
    2024-01-15-incident.md

---
type: skill
tags: [database, timeout]
confidence: pattern
status: active
---

# Timeout Diagnosis

Description of the skill...

## Evidence
- [[episodic/2024-01-15-incident]]: First observed during outage

## Related
- [[concept/connection-pooling]]

Frontmatter Fields

Field	Required	Values
`type`	Yes	`skill`, `episodic`, `concept`, `failure-pattern`, `system-knowledge`
`confidence`	Yes	`fact`, `pattern`, `heuristic`
`tags`	No	Free-form string list
`status`	Auto	`active`, `superseded`, `archived`

Tools

Write & Edit

Tool	Description
`vault_write(path, frontmatter, body)`	Create or overwrite a note
`vault_write_batch(entries)`	Write multiple notes atomically
`vault_edit(path, operation, params)`	Incremental edit (4 operations below)
`vault_delete(path)`	Delete a note
`vault_rename(old_path, new_path)`	Rename + auto-rewrite all backlinks

Edit Operations

Operation	Params	Use
`replace_string`	`{"old": "...", "new": "..."}`	Inline corrections
`set_frontmatter`	`{"confidence": "fact"}`	Update metadata
`replace_section`	`{"heading": "## Evidence", "body": "..."}`	Rewrite a section
`append_section`	`{"heading": "## Evidence", "content": "..."}`	Append to a section

Read & Browse

Tool	Description
`vault_read(path)`	Read frontmatter + body
`vault_list(path, depth, type_filter)`	Browse directory

Search & Discovery

Tool	Description
`vault_search(query, filters, mode, limit)`	FTS5 / semantic / hybrid search
`vault_backlinks(path)`	Who links to this note
`vault_traverse(start, depth, direction)`	BFS graph traversal with directed edges
`vault_lint()`	Find dead links + orphan notes

Validation

Every write/edit automatically checks and returns warnings:

Required frontmatter fields (type, confidence)
Valid enum values
H1 heading present in body
All [[wikilinks]] resolve to existing notes

The write succeeds regardless — warnings are informational for the agent to decide whether to fix.

Architecture

.md files (source of truth, git-trackable)
    │
    ▼
.vault.db (SQLite index, auto-rebuilt if deleted)
    ├── notes       — YAML frontmatter metadata
    ├── notes_fts   — FTS5 full-text search
    ├── links       — [[wikilink]] directed graph
    ├── tags        — tag index
    └── notes_vec   — embedding vectors (optional)

License

MIT

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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