kb-mcp-lite 0.4.0

Lightweight agent-native knowledge base. SQLite + FTS5 + vec0 + MCP server.

kb-mcp

An agent-native knowledge base.

pip install kb-mcp — give any LLM agent a structured, queryable, local-first second brain.

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The problem

Knowledge bases for humans (Notion, Obsidian) and for search engines (Elasticsearch, vector DBs) leave a gap: LLM agents need a knowledge layer that speaks their protocol and assumes the reader is a model, not a person.

kb-mcp fills it.

	Obsidian / Notion	Vector DBs (Chroma / LanceDB)	kb-mcp
Reader-optimised for	Humans	Embeddings	LLM agents
Protocol	Web UI	SDK	MCP (stdio)
Schema	Free-form	Free-form	Typed (project / decision / lesson / ...)
Default storage	Cloud / proprietary	Local files	SQLite + FTS5
Setup	Sign up	pip install + configure	pip install and go

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Features

• 🧠 Agent-native. Every document is reachable from any MCP client via 12 tools, 4 Resources, and 2 Prompts.
• 📐 Schema-first. Six built-in document types (project, decision, lesson, glossary, person, faq) — extensible via Python subclassing.
• 🔍 Full-text search. Three modes: lexical (BM25), fuzzy (trigram), and hybrid (combined). Optional semantic search with sqlite-vec.
• 📜 Version history. Every create/update/delete is recorded. Restore any previous version, diff between versions, or recover soft-deleted docs.
• 🔗 Typed links. Documents reference other documents; backlinks are automatic.
• 📝 Markdown friendly. Round-trip import/export with frontmatter. Aliases let agents reference the same doc from different contexts.
• 🗄️ Multi-vault. Isolated knowledge bases per project or team. Switch between vaults with kb vault switch.
• 🪶 Zero deps by default. SQLite ships with Python. pip install kb-mcp and you're done.
• 🔒 Local-first. Your data stays on your machine. No cloud, no telemetry, no phone-home.

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Quickstart

pip install kb-mcp
kb init
kb add --type project --title "kb-mcp" --tags kb,mcp,open-source --body "Agent-native knowledge base."
kb search "mcp server"

# Expose to any MCP client
kb serve

That's it. Five commands, zero config files.

👉 Full walkthrough: docs/quickstart.md

Vault quickstart (multi-space)

# Create isolated knowledge bases
kb vault create work --desc "Work projects"
kb vault create personal --desc "Personal learning"

# Switch between them
kb vault switch work
kb add --type project --title "My Work App" --body "..."

kb vault switch personal
kb add --type lesson --title "Rust tutorial notes" --body "..."

# Each vault has its own SQLite database
kb vault list

Team sync (Git)

Share a team vault via any Git remote:

# A member: set up
kb vault create team --desc "Team shared knowledge"
kb vault init-git                     # git init + .gitignore
kb vault commit -m "Initial KB"       # export → git commit
kb vault push origin main             # push to remote

# B member: clone and start using
git clone <remote-url> ~/.local/share/kb-mcp-custom/
KB_MCP_HOME=~/.local/share/kb-mcp-custom kb vault list
KB_MCP_HOME=~/.local/share/kb-mcp-custom kb vault pull    # pull → import

# Daily workflow:
# Make changes...
kb add --type decision --title "Use SQLite FTS5"
# Share:
kb vault commit -m "Add ADR about FTS5"
kb vault push

# Get teammates' changes:
kb vault pull

The sync is text-based: the vault's Markdown files go to a md/ subdirectory under Git, while the binary .db stays local and .gitignored.

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Document types

Type	Purpose	Example
project	Repo / initiative background	kb-mcp, micro-app-fork
decision	Architecture Decision Record (ADR)	"Use SQLite FTS5 over Elasticsearch"
lesson	Post-mortem / lessons learned	"Don't last_insert_rowid() across multi-INSERT batches"
glossary	Term definitions	FTS5, MCP, ADR
person	People the agent should recognise	"Zhang Bei, owner, uses Hermes"
faq	Frequently asked questions	"Why SQLite?"

Subclass kb_mcp.schema.Document to add your own.

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MCP integration

Add to ~/.config/claude_desktop_config.json (or any MCP client):

{
  "mcpServers": {
    "kb": {
      "command": "kb",
      "args": ["serve"]
    }
  }
}

The agent sees 12 tools:

Tool	Description
kb_search	Full-text search (lexical / fuzzy / hybrid)
kb_get	Fetch document by id (also resolves aliases)
kb_add	Create a new document
kb_update	Patch fields on an existing document
kb_delete	Soft-delete a document
kb_list	Browse documents with type/tag filters
kb_link	Create a typed edge between documents
kb_unlink	Remove typed edges
kb_history	View document version history
kb_restore	Restore to a previous version
kb_diff	Field-level diff between versions
kb_restore_deleted	Restore a soft-deleted document

... plus 4 Resources (kb://doc/, kb://search/, kb://links/, kb://doctor) and 2 Prompts (new-doc, search-expert) for richer agent interaction.

You can also serve a specific vault:

kb serve --vault project-x

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Development

git clone https://github.com/your-org/kb-mcp
cd kb-mcp
pip install -e ".[dev]"
pytest          # unit + E2E (real SQLite temp file, no mocks)
ruff check .
mypy src/

👉 Spec: docs/requirements.md · Architecture: docs/architecture.md · CLI reference: docs/cli-reference.md

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Roadmap

Version	Scope	Status
v0.1.0	CLI + MCP server + SQLite/FTS5 + 6 doc types + Markdown I/O	✅ shipped
v0.2.0	Fuzzy/trigram search, semantic search (sqlite-vec), tools/CLI completion	✅ shipped
v0.3.0	MCP Resources & Prompts, version history (restore/diff), aliases	✅ shipped
v0.4.0	Multi-vault (isolated knowledge bases), vault CLI + MCP vault selection	✅ shipped
v0.5.0	Local embedding models, CJK tokenizer, knowledge graph visualization	exploring
v0.6.0	Plugin system, external sync (Notion/GitHub), LLM-native enhancements	exploring
v1.0.0	Postgres backend, multi-user auth, hosted mode	exploring

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Status

beta. The API and storage format are stable since v0.3.0. Pin minor versions (kb-mcp>=0.3,<0.5) in production if you prefer conservative upgrades.

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Contributing

Issues and PRs welcome. See CONTRIBUTING.md.

By participating, you agree to abide by the Code of Conduct.

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License

MIT — do what you want, just keep the copyright notice.