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mcpforge

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mcpforge

Erstelle einen MCP-Server in 5 Zeilen Python.

Python License: MIT Status MCP

Before                              After
──────                              ─────
~200 lines of                       @serve
JSON-RPC stdio                      class MarketTools:
boilerplate, schema                     @tool
generation, error                       def latest_price(self, symbol: str) -> float: ...
handling, lifecycle                     @tool
management.                             def search(self, query: str) -> list[dict]: ...

                                    $ python -m mcpforge run market:MarketTools
                                    ✓ MCP server running on stdio

Warum mcpforge

Das Model Context Protocol (MCP) ist der offene Standard, den Claude, Cursor und ein explodierendes Ökosystem von KI-Tools verwenden, um externe Funktionen aufzurufen. Es ist mächtig — und das Schreiben eines Servers ist derzeit mühsam.

Du schreibst bei jedem Projekt dasselbe JSON-RPC-Framing, die Schema-Generierung, die Dispatch-Schleife und die Fehlerbehandlung. mcpforge löscht das alles. Annotiere deine Klasse. Gib deinen Methoden Typ-Hinweise. Fertig.

from mcpforge import serve, tool

@serve(name="market_tools", version="0.1.0")
class MarketTools:
    """Market data tools for AI agents."""

    @tool(description="Get the latest price for a symbol")
    def latest_price(self, symbol: str) -> float:
        return fetch_price(symbol)

    @tool
    def search(self, query: str, limit: int = 10) -> list[dict]:
        """Search ticker symbols matching `query`."""
        return run_search(query, limit)

Das ist ein vollständiger, spezifikationskonformer MCP-Server. Typ-Hinweise werden zu JSON-Schemas. Docstrings werden zu Tool-Beschreibungen. Rückgabewerte werden automatisch serialisiert.

Related MCP server: nbmcp

60-Sekunden-Schnellstart

pip install mcpforge
# hello.py
from mcpforge import serve, tool

@serve(name="hello", version="0.1.0")
class HelloTools:
    @tool
    def greet(self, name: str = "world") -> str:
        """Say hello to someone."""
        return f"Hello, {name}!"
python -m mcpforge run hello:HelloTools

Du hast jetzt einen funktionierenden MCP-Server, der JSON-RPC 2.0 über stdio spricht.

Wie es funktioniert

  1. @serve markiert eine Klasse als MCP-Server (Name, Version, Fähigkeiten).

  2. @tool registriert Methoden als MCP-Tools.

  3. @resource(uri=...) registriert Methoden als MCP-Ressourcen.

  4. mcpforge untersucht die Signatur jeder Methode und erstellt ein JSON-Schema — Primitive, list[T], dict[str, T], Literal[...], Optional[T], Dataclasses und Pydantic-Modelle funktionieren einfach.

  5. python -m mcpforge run mod:Class startet die stdio-Schleife, verarbeitet initialize / tools/list / tools/call / resources/list / resources/read, und meldet JSON-RPC-Fehler mit den korrekten Codes.

Kein externes MCP-SDK. Nur Standardbibliothek json + pydantic für Schema-Annehmlichkeiten.

Integrierte Server

Zwei "Batteries-included"-Server, die du heute sofort einsetzen kannst:

# Filesystem tools (sandboxed to a root directory)
python -m mcpforge run mcpforge.builtin.filesystem:FilesystemTools

# HTTP fetch tools
python -m mcpforge run mcpforge.builtin.http:HttpTools

FilesystemTools stellt list_dir, read_file, search bereit — in einer Sandbox mit Pfad-Traversal-Prüfungen. HttpTools stellt fetch_url mit Größenbeschränkungen bereit.

Einbindung in Claude Desktop

Füge dies zu ~/Library/Application Support/Claude/claude_desktop_config.json hinzu:

{
  "mcpServers": {
    "market": {
      "command": "python",
      "args": ["-m", "mcpforge", "run", "market:MarketTools"],
      "cwd": "/path/to/your/project"
    }
  }
}

Starte Claude Desktop neu. Deine Tools erscheinen im Chat.

Einbindung in Cursor

~/.cursor/mcp.json:

{
  "mcpServers": {
    "market": {
      "command": "python",
      "args": ["-m", "mcpforge", "run", "market:MarketTools"]
    }
  }
}

Vergleich

Funktion

mcpforge

mcp SDK

FastMCP

Manuell

Einzelner Decorator

Ja

Nein

Ja

Nein

Auto JSON Schema aus Typen

Ja

Nein

Ja

Nein

Pydantic v2 Unterstützung

Ja

Ja

Ja

Nein

Keine weiteren Abhängigkeiten

Ja

Nein

Nein

N/A

Integrierte fs / http Server

Ja

Nein

Nein

Nein

Zeilen für Hello World

~5

~40

~10

~200

Überprüfung des Wire-Formats

python -m mcpforge inspect market:MarketTools

Gibt die exakte tools/list-Payload aus, die deine Clients sehen werden.

Roadmap

  • [x] Tools (call, list)

  • [x] Ressourcen (read, list)

  • [x] Typ-Hinweis -> JSON Schema (Pydantic v2, dataclasses, Literal, Optional)

  • [x] Integrierte Dateisystem- und HTTP-Server

  • [ ] Ressourcen-Abonnements

  • [ ] Prompts-Fähigkeit

  • [ ] Sampling-Fähigkeit

  • [ ] WebSocket / HTTP-SSE Transport (optional [http] extra)

  • [ ] Asynchrone Tools (async def)

  • [ ] OTel Tracing-Hooks

Lizenz

MIT — siehe LICENSE.

Autor: thechifura. Geschwisterprojekt von quantflow und strategos.

Available Tools

3 tools
list_dirA

List entries in path (relative to the sandbox root).

ParametersJSON Schema
NameRequiredDescriptionDefault
pathNo.

TDQS

A3.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description bears full burden. It does not disclose what types of entries are listed (files, directories), sorting order, or any other behavioral traits beyond listing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no wasted words. Verb is front-loaded, and the essential context is included efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple listing tool with one parameter and no output schema, the description is adequate but could be more complete by noting whether entries include both files and directories.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage, but description adds meaning by specifying that path is relative to the sandbox root. This clarifies a key detail not in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'list', the resource 'entries in path', and adds context 'relative to the sandbox root'. It distinguishes from sibling tools read_file and search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives or exclusions. The description does not mention any context or conditions for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

read_fileA

Read up to max_bytes bytes of the file at path as UTF-8 text.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYes
max_bytesNo

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that it reads up to max_bytes as UTF-8 text, but does not mention error behavior (e.g., file not found, binary files) or performance implications. With no annotations, the description provides moderate transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently covers the tool's core functionality without extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and sibling tools, the description could mention return value format or error handling. It adequately covers the main behavior but lacks completeness for a file reading tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains both parameters: path is the file location, max_bytes limits the bytes read, and specifies UTF-8 encoding. However, it does not clarify path format (absolute/relative).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it reads a file at a given path, up to a specified number of bytes, as UTF-8 text. It distinguishes from sibling tools 'list_dir' (listing directory contents) and 'search' (searching for files).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of when not to use it or any prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updatesv0.1.0
    • First observedlist_dir
    • First observedread_file
    • First observedsearch
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

B3.3/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: listing directory entries, reading file contents, and searching for patterns. No overlap in functionality.

Naming Consistency4/5

Naming is mainly verb_noun (list_dir, read_file) with one tool using a single verb (search). All use consistent snake_case, but slight pattern deviation prevents a perfect score.

Tool Count5/5

Three tools is a reasonable and focused set for basic file operations within a sandbox. Each tool serves a distinct and necessary function.

Completeness2/5

Only read-only operations are provided. Missing write, update, or delete tools, which are essential for a file manipulation server, leaving significant gaps.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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