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Mcpserve Py

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Exposes SQLite database query tools and markdown document resources over JSON-RPC 2.0 stdio transport, enabling AI assistants to read and search documents and e

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Описание

Exposes SQLite database query tools and markdown document resources over JSON-RPC 2.0 stdio transport, enabling AI assistants to read and search documents and execute read-only SQL queries.

README

CI Python 3.11+ License: MIT

A Model Context Protocol (MCP) server built in Python — exposes database query tools and document resources over JSON-RPC 2.0 stdio transport, enabling AI assistants to interact with SQLite databases and markdown documents.

What is MCP?

The Model Context Protocol is an open standard for connecting AI assistants to external tools and data sources. MCP servers expose tools (functions the AI can call) and resources (data the AI can read) over a JSON-RPC 2.0 transport.

This server implements the MCP protocol from scratch using raw JSON-RPC 2.0 over stdio — no SDK dependency required.

Features

  • 🔧 8 tools — database queries, document CRUD, search, date/time
  • 📄 Resource providers — documents and database schemas as readable resources
  • 🛡️ SQL injection protection — only SELECT queries allowed, with regex validation
  • 📝 YAML frontmatter — documents stored as markdown with structured metadata
  • 🔌 Stdio transport — line-delimited JSON-RPC 2.0 over stdin/stdout
  • Zero SDK dependency — hand-rolled MCP protocol implementation
  • Well-tested — 113 tests covering protocol, tools, resources, and integration

Quick Start

# Clone and install
git clone https://github.com/devaloi/mcpserve-py.git
cd mcpserve-py
pip install -e ".[dev]"

# Run the server
python -m mcpserve_py

# Run tests
python -m pytest -v

Environment Variables

Variable Default Description
MCPSERVE_DATA_DIR data Directory for documents and data
MCPSERVE_DB_PATH data/mcpserve.db Path to SQLite database
MCPSERVE_LOG_LEVEL INFO Log level (DEBUG, INFO, WARNING, ERROR)

Claude Desktop Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "mcpserve-py": {
      "command": "python",
      "args": ["-m", "mcpserve_py"],
      "env": {
        "MCPSERVE_DATA_DIR": "./data",
        "MCPSERVE_DB_PATH": "./data/mcpserve.db"
      }
    }
  }
}

Tools

Tool Description Parameters
query_database Execute read-only SQL query sql: str, params?: list
list_tables List all tables in database
describe_table Get table schema table: str
create_document Create a markdown document title: str, content: str, tags?: list[str]
read_document Read document by title title: str
list_documents List all documents tag?: str
search_documents Full-text search across documents query: str
get_datetime Current date/time timezone?: str

Resources

URI Pattern Description MIME Type
docs:///{title} Document content text/markdown
db:///schema Full database schema text/plain
db:///tables/{name} Single table schema text/plain

Architecture

src/mcpserve_py/
├── __main__.py          # Entry point: python -m mcpserve_py
├── server.py            # MCP server: receive → dispatch → respond
├── protocol.py          # JSON-RPC 2.0 types and encoding
├── transport.py         # Stdio transport (line-delimited JSON)
├── config.py            # Pydantic settings
├── tools/
│   ├── registry.py      # Tool registry
│   ├── database.py      # SQLite tools (query, list_tables, describe)
│   ├── documents.py     # Document tools (CRUD + search)
│   └── system.py        # System tools (get_datetime)
└── resources/
    ├── provider.py      # Resource provider interface + registry
    ├── documents.py     # Document resource provider
    └── database.py      # Database schema resource provider

Design Decisions

  • No MCP SDK — The protocol is implemented directly using JSON-RPC 2.0 dataclasses. This demonstrates deep understanding of the protocol rather than SDK usage.
  • Synchronous — Stdio is inherently sequential; async adds complexity without benefit here.
  • Pydantic Settings — Configuration via environment variables with type validation and .env file support.
  • Tool registry pattern — Tools register themselves with a central registry, keeping the server dispatch clean.
  • Read-only SQL — Mutations are rejected via regex before reaching SQLite, preventing data corruption by AI assistants.
  • YAML frontmatter — Documents use the same format as static site generators (Jekyll, Hugo), making them human-readable and tool-friendly.

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
make test

# Lint
make lint

# Type check
make typecheck

# Format
make format

# All checks
make all

License

MIT

Contributing

See CONTRIBUTING.md. PRs welcome — run make all before submitting.

from github.com/devaloi/mcpserve-py

Установить Mcpserve Py в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install mcpserve-py

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add mcpserve-py -- uvx --from git+https://github.com/devaloi/mcpserve-py mcpserve-py

FAQ

Mcpserve Py MCP бесплатный?

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

Нужен ли API-ключ для Mcpserve Py?

Нет, Mcpserve Py работает без API-ключей и переменных окружения.

Mcpserve Py — hosted или self-hosted?

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

Как установить Mcpserve Py в Claude Desktop, Claude Code или Cursor?

Открой Mcpserve Py 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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