mcp-toolforge
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-toolforgeCreate a weather MCP server with a tool that fetches temperature for a city and returns a summary."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-toolforge
A meta-MCP server that generates new MCP servers from natural-language tool descriptions.
Given a project name, a short description, and a list of natural-language tool
descriptions (e.g. "fetches the weather for a string city and returns a string summary"),
mcp-toolforge writes a complete, runnable MCP server project — schema, implementation,
tests with real assertions, README, LICENSE — ready to install and run.
flowchart TD
subgraph Client_Layer["AI Client / Claude Desktop"]
A["Client (Claude, Cursor, etc.)"]
end
subgraph Meta_Server["mcp-toolforge (this repo)"]
M["mcp_toolforge.server"]
G["mcp_toolforge.generator"]
end
subgraph Generated["Generated Server Project"]
P["src/<pkg>/__init__.py"]
S["src/<pkg>/server.py"]
T["tests/test_<pkg>.py"]
R["README.md"]
L["LICENSE"]
PP["pyproject.toml"]
end
A -- "MCP stdio JSON-RPC" --> M
M -- "generate_server tool call" --> G
G -- "writes files" --> P
G -- "writes files" --> S
G -- "writes files" --> T
G -- "writes files" --> R
G -- "writes files" --> L
G -- "writes files" --> PPArchitecture
┌─────────────────────┐ ┌──────────────────────────┐
│ AI Client │ stdio │ mcp-toolforge server │
│ (Claude, Cursor) │──JSON──│ (this repo) │
└─────────────────────┘ RPC └────────┬───────────────┘
│ generate_server
│ (name, description,
│ tool_descriptions, dest)
▼
┌────────────────────────────────────┐
│ generator.generate_project() │
│ parses NL → ToolSpec → ServerSpec │
│ renders: pyproject, server.py, │
│ tests, README, LICENSE │
└────────────────────────────────────┘
│
┌─────────────────┴─────────────────┐
│ Example generated servers │
│ • examples/weather_server │
│ • examples/todo_server │
│ • examples/math_server │
└────────────────────────────────────┘Related MCP server: MCP Server Generator
Quickstart
Install mcp-toolforge
pip install -e ".[dev]"Run mcp-toolforge itself (meta-server)
As an MCP server (stdio transport):
{
"mcpServers": {
"mcp-toolforge": {
"command": "python",
"args": ["-m", "mcp_toolforge.server"],
"cwd": "/path/to/mcp-toolforge"
}
}
}Or as a CLI that generates a standalone server project:
# Interactive wizard
mcp-toolforge -i
# One-shot
mcp-toolforge \
--name my_server \
--description "A server that does X" \
--tool "fetches the weather for a string city and returns a string summary" \
--dest ./my_serverUsing the generate_server tool
When mcp-toolforge is registered as an MCP server, an AI agent can call:
generate_server(
name="my_server",
description="A server that does X",
tool_descriptions=[
"fetches the weather for a string city and returns a string summary",
"adds a string task and returns a string confirmation"
],
dest="/path/to/output" # optional, defaults to /tmp/mcp-toolforge-gen
)The tool writes a complete project to dest/<package_name>/ and returns a
summary string. The generated server can then be installed and registered
with your MCP client independently.
How natural-language parsing works
Each tool description should follow the pattern:
<VERB> [a/an] <type> <name> [, <type> <name>] ... and returns <type> <description>Examples:
Description | Tool name | Params |
|
|
|
|
|
|
|
|
|
|
|
|
Recognized parameter types: string, integer, number, boolean, array.
If no typed parameters are detected, a free-form query: string parameter is
inferred.
Examples
Three example servers are generated into examples/:
Server | Package | Tools | Description |
WeatherServer |
|
| Fetches weather info |
TodoServer |
|
| Manages a todo list |
MathServer |
|
| Arithmetic tools |
Each example is a fully working MCP server with its own tests:
cd examples/math_server
pip install -e .
pytestDevelopment
# Install with dev dependencies
pip install -e ".[dev]"
# Run all tests
pytest
# Run end-to-end test against the meta-server over stdio
python e2e_test.py
# Regenerate examples
python make_examples.pyTesting
tests/test_generator.py— 16 tests for the generator (parsing, schema inference, file rendering, project creation)tests/test_server.py— 5 tests for the meta-MCP server (tool listing, tool calling, error handling)e2e_test.py— end-to-end test that runs the meta-server as a real stdio subprocess and connects with an MCPClientEach example server ships with 4 tests (12 total across 3 examples)
All tests use real assertions and verify actual file output / tool results.
License
MIT — see LICENSE.
This server cannot be deployed
Maintenance
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MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.
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