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Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketi

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Описание

Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

README

Universal MCP knowledge server for LLM agents, powered by local RAG.

Use Canon to provide domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

Typical workflows:

  • Find the most suitable guide for a task
  • Retrieve concise best-practice snippets
  • Read full guides for deeper execution context

Quick Start

Install in Cursor

Go to: Settings -> Cursor Settings -> MCP -> Add new global MCP server

Pasting the following configuration into your Cursor ~/.cursor/mcp.json file is the recommended approach. You may also install in a specific project by creating .cursor/mcp.json in your project folder. See Cursor MCP docs for more info.

Cursor Local Connection

{
  "mcpServers": {
    "canon": {
      "command": "uvx",
      "args": ["mcp-canon"]
    }
  }
}

Cursor Local Connection With Custom Database

{
  "mcpServers": {
    "canon": {
      "command": "uvx",
      "args": ["mcp-canon"],
      "env": {
        "CANON_DB_PATH": "/path/to/my-db"
      }
    }
  }
}

Cursor Remote Server Connection

{
  "mcpServers": {
    "canon": {
      "url": "http://localhost:8080/mcp"
    }
  }
}
Install in Claude Code

Run this command. See Claude Code MCP docs for more info.

Claude Code Local Connection

claude mcp add --scope user canon -- uvx mcp-canon

Cursor Local Connection With Custom Database

claude mcp add --scope user -e CANON_DB_PATH=/path/to/my-db canon -- uvx mcp-canon

Claude Code Remote Server Connection

claude mcp add --scope user --transport http canon http://localhost:8080/mcp

Remove --scope user to install for the current project only.

Install in Opencode

Add this to your Opencode configuration file. See Opencode MCP docs for more info.

Opencode Local Connection

{
  "mcp": {
    "canon": {
      "type": "local",
      "command": ["uvx", "mcp-canon"],
      "enabled": true
    }
  }
}

Opencode Local Connection With Custom Database

{
  "mcp": {
    "canon": {
      "type": "local",
      "command": ["uvx", "mcp-canon"],
      "enabled": true,
      "environment": {
        "CANON_DB_PATH": "/path/to/my-db"
      }
    }
  }
}

Opencode Remote Server Connection

"mcp": {
  "context7": {
    "type": "remote",
    "url": "http://localhost:8080/mcp",
    "enabled": true
  }
}
Install in Gemini CLI

Run this command. See Gemini CLI MCP docs for more info.

Gemini CLI Local Connection

gemini mcp add --scope user canon uvx mcp-canon

Gemini CLI Local Connection With Custom Database

gemini mcp add --scope user -e CANON_DB_PATH=/path/to/my-db canon uvx mcp-canon

Gemini CLI Remote Server Connection

gemini mcp add --scope user --transport http canon http://localhost:8080/mcp

Remove --scope user to install for the current project only.

Install in Google Antigravity

Go to the agent panel and open: ... -> MCP Servers -> Manage MCP Servers -> View raw config. Add this to your mcp_config.json file. See Google Antigravity MCP docs for more info.

Google Antigravity Local Connection

{
  "mcpServers": {
    "canon": {
      "command": "uvx",
      "args": ["mcp-canon"]
    }
  }
}

Google Antigravity Local Connection With Custom Database

{
  "mcpServers": {
    "canon": {
      "command": "uvx",
      "args": ["mcp-canon"],
      "env": {
        "CANON_DB_PATH": "/path/to/my-db"
      }
    }
  }
}

Create and index your own guides

Complete workflow from installation to running with your own domain guides.

Step 1: Install with indexing support

pip install "mcp-canon[indexing]"

Step 2: Create library structure

my-library/
├── engineering/
│   └── python-fastapi-guide/
│       ├── INDEX.md      # Required: metadata
│       └── GUIDE.md      # Content
├── marketing/
│   └── launch-playbook/
│       ├── INDEX.md
│       └── GUIDE.md
└── video-editing/
    └── shorts-workflow/
        └── INDEX.md      # Can reference external URL

Step 3: Create guides

Step 4: Index your library

# Index to custom location
canon index --library ./my-library --output /path/to/my-db

# Validate frontmatter before indexing (optional)
canon validate --library ./my-library

Running as HTTP server

For remote access or multi-client scenarios, run Canon as an HTTP server. This is useful when multiple agents or teams share one cross-domain knowledge base.

Step 1: Install with HTTP support

pip install "mcp-canon[http]"

Step 2: Start the server

# Default port 8080
canon serve

# Custom port and host
canon serve --port 3000 --host 0.0.0.0

# With custom database
CANON_DB_PATH=/path/to/db canon serve --port 8080

Step 3: Configure MCP client

{
  "mcpServers": {
    "canon": {
      "url": "http://localhost:8080/mcp"
    }
  }
}

Environment Variables

Variable Description Default
CANON_DB_PATH Path to custom database Bundled DB
CANON_EMBEDDING_MODEL Fastembed model name (supported models) nomic-ai/nomic-embed-text-v1.5-Q
CANON_EMBEDDING_DIM Embedding vector dimensions (must match model) 768
CANON_FASTEMBED_THREADS ONNX runtime threads for FastEmbed (lower = less RAM, slower) auto
CANON_FASTEMBED_BATCH_SIZE Embedding batch size during indexing (lower = less RAM, slower) 256
CANON_FASTEMBED_PARALLEL FastEmbed data-parallel workers (>1 increases RAM usage) disabled
CANON_LOG_LEVEL Log level (DEBUG, INFO, WARNING, ERROR) INFO
CANON_LOG_JSON Output logs in JSON format false

Note: Changing CANON_EMBEDDING_MODEL or CANON_EMBEDDING_DIM requires a full reindex: canon index --library ./library

Change embedding model and dimensions

Internal constants EMBEDDING_MODEL_NAME and EMBEDDING_DIM are configured via:

  • CANON_EMBEDDING_MODEL
  • CANON_EMBEDDING_DIM

Example (using BAAI/bge-small-en-v1.5, 384 dims):

CANON_EMBEDDING_MODEL=BAAI/bge-small-en-v1.5 \
CANON_EMBEDDING_DIM=384 \
canon index --library ./library --output ./my-db

Where to find available models:

Important:

  • CANON_EMBEDDING_DIM must match the selected model output size.
  • After changing model or dimension, rebuild the index before running search/server commands.

MCP Tools

Tool Description
search_best_practices Semantic search for best practices in any domain (optionally scoped by guide_id)
search_suitable_guides Find guides that match a task description across domains
read_full_guide Get complete guide content for full context

CLI Commands

# Indexing
canon index --library ./library           # Index guides from any domain (creates new DB)
canon index --library ./lib --append      # Add to existing database
canon validate --library ./library        # Validate frontmatter

# Server
canon serve --port 8080                   # Start HTTP server (requires [http])

# Info
canon list                                # List indexed guides
canon info                                # Show database info

License

MIT

from github.com/tripcher/canon

Установка Canon

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/tripcher/canon

FAQ

Canon MCP бесплатный?

Да, Canon MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Canon?

Нет, Canon работает без API-ключей и переменных окружения.

Canon — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Canon в Claude Desktop, Claude Code или Cursor?

Открой Canon на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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