Memory Vault MCP Server — Markdown + SQLite knowledge store with bidirectional [[wikilinks]] for AI agents
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"vault-mcp-2","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# 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 ```bash uvx vault-mcp # run directly without install pip install vault-mcp # core (keyword search only) pip install "vault-mcp[semantic]" # + embedding-based semantic search ``` ## Running the MCP Server ```bash # 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 ```bash claude mcp add vault -- vault-mcp ``` Or `.mcp.json`: ```json { "mcpServers": { "vault": { "type": "stdio", "command": "vault-mcp", "env": { "VAULT_DIR": "./vault" } } } } ``` ### Cursor / Windsurf / Other MCP Clients Add to your MCP settings: ```json { "vault": { "command": "vault-mcp", "env": { "VAULT_DIR": "./vault" } } } ``` ### Python Library (no MCP) ```python 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-incid…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.