# mMCP
## Motivation
`mmcp` is inspired by Anthropic's MCP-based `create-python-server` with the following changes:
- Microservices architecture
- Docker baked-in for immediate deployment
- CLI tooling for ease-of-use (e.g., `mmcp add tool`)
- Added support for Poetry
The purpose of this project is to provide a more streamlined and user-friendly experience for creating SSE-specific MCP servers, foregrounding deployment options in order to make it easier to get started with MCP. In sum, it began and ended as a means to satisfy my own needs from the MCP.
## Quickstart
```bash
>> pip install mmcp
>> mmcp create-mmcp --name my-mmcp-server
>> cd my-mmcp-server
>> mmcp run server
```
To add a tool, use the following command:
```bash
>> mmcp add tool --name my-tool
```
Refer to the project structure for more information, where `mmcp add tool` will add a tool to the `tools/` directory.
```
- MY_MMCP_SERVER/
- src/
- my_mmcp_server/
- prompts/ # Prompt-definition code
- resources/ # Resource-definition code
- services/ # Service-layer code
- __init__.py
- prompts.py
- resources.py
- tools.py
- tools/ # Tool-definition code
- __init__.py
- base.py
- my_tool.py # <-- Added by `mmcp add tool --name my_tool`
- __init__.py
- app.py
- server.py
- tests/
- .env
- docker-compose.yml
- Dockerfile # Docker image definition
- pyproject.toml
- README.md
```
The `services/` layer orchestrates the `mcp`-specific decorators, employed generically via `server.py`:
```python
@server.list_tools()
async def handle_list_tools():
return await tool_service.list_tools()
@server.call_tool()
async def handle_call_tool(name: str, arguments: dict | None):
return await tool_service.execute_tool(name, arguments or {})
```
where `@server` is:
```python
from mcp.server import Server
# Create the server instance
server = Server("my_mmcp_server")
```
## Usage
To run the project, use the following command:
```bash
>> mmcp run server
```
which launches the server via `poetry run python -m my_server.server`.
A common pattern to route calls to the server via an endpoint.
Suppose your server is running on `http://127.0.0.1:8080/sse`:
```python
from mcp.client.session import ClientSession
from mcp.client.sse import sse_client
# ...fastapi setup
# ...
@router.get("/mcp-list-tools")
async def mcp_list_tools():
async with sse_client(url="http://127.0.0.1:8080/sse") as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
return tools
@router.post("/mcp-call-tool")
async def mcp_call_tool(tool_name: str, parameters: Dict[str, Any]):
async with sse_client(url="http://127.0.0.1:8080/sse") as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
# # Call the fetch tool
# result = await session.call_tool("fetch", {"url": "https://example.com"})
result = await session.call_tool(tool_name, parameters)
return result
```
Additionally, the `tests/test_mcp_list_tools.py` file can be run to test the `list_tools` method, for a sanity check. Just make sure the server is running.
**Note:** More extensive documentation and usage is on the way.
## Development
To run the project, use the following command:
```bash
>> poetry install --no-cache
>> poetry shell
>> poetry run mmcp create-mmcp --name my_project
```
To build and run the project, use the following command:
```bash
>> cd path/to/your/mmcp
>> python -m build
>> pip install "path/.../dist/mmcp-0.1.0.whl"
```
## License
This project is licensed under the MIT License. See [LICENSE](LICENSE) for details.
**NOTE**
This project is based on [create-python-server](https://github.com/modelcontextprotocol/create-python-server) by Anthropic, PBC.
This project is not affiliated with Anthropic, PBC., and does not reflect my views or opinions on the strengths or weaknesses of Anthropic's MCP.
Raw data
{
"_id": null,
"home_page": null,
"name": "mmcp",
"maintainer": "Richard Scheiwe",
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": "rscheiwe.dev@gmail.com",
"keywords": "mcp, llm, automation, sse, server, template, low-code, microservice, api, generative-ai, ai",
"author": "Richard S.",
"author_email": "rscheiwe.dev@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/0b/ec/6b890a6d068a6a1fcea0f68aba743fba63cc4dda34e4e3b3360b0c7323bb/mmcp-0.1.0.tar.gz",
"platform": null,
"description": "# mMCP\n\n## Motivation\n`mmcp` is inspired by Anthropic's MCP-based `create-python-server` with the following changes:\n\n- Microservices architecture\n- Docker baked-in for immediate deployment\n- CLI tooling for ease-of-use (e.g., `mmcp add tool`)\n- Added support for Poetry\n\nThe purpose of this project is to provide a more streamlined and user-friendly experience for creating SSE-specific MCP servers, foregrounding deployment options in order to make it easier to get started with MCP. In sum, it began and ended as a means to satisfy my own needs from the MCP.\n\n## Quickstart\n\n```bash\n>> pip install mmcp\n>> mmcp create-mmcp --name my-mmcp-server\n>> cd my-mmcp-server\n>> mmcp run server\n```\n\nTo add a tool, use the following command:\n\n```bash\n>> mmcp add tool --name my-tool\n```\n\nRefer to the project structure for more information, where `mmcp add tool` will add a tool to the `tools/` directory.\n\n```\n- MY_MMCP_SERVER/\n - src/\n - my_mmcp_server/\n - prompts/ # Prompt-definition code\n - resources/ # Resource-definition code\n - services/ # Service-layer code\n - __init__.py\n - prompts.py\n - resources.py\n - tools.py\n - tools/ # Tool-definition code\n - __init__.py\n - base.py\n - my_tool.py # <-- Added by `mmcp add tool --name my_tool`\n - __init__.py\n - app.py\n - server.py\n - tests/\n - .env\n - docker-compose.yml\n - Dockerfile # Docker image definition\n - pyproject.toml\n - README.md\n```\n\nThe `services/` layer orchestrates the `mcp`-specific decorators, employed generically via `server.py`:\n\n```python\n@server.list_tools()\nasync def handle_list_tools():\n return await tool_service.list_tools()\n\n@server.call_tool()\nasync def handle_call_tool(name: str, arguments: dict | None):\n return await tool_service.execute_tool(name, arguments or {})\n\n```\n\nwhere `@server` is:\n\n```python\nfrom mcp.server import Server\n\n# Create the server instance\nserver = Server(\"my_mmcp_server\")\n```\n\n## Usage\n\nTo run the project, use the following command:\n\n```bash\n>> mmcp run server\n```\n\nwhich launches the server via `poetry run python -m my_server.server`.\n\nA common pattern to route calls to the server via an endpoint. \n\nSuppose your server is running on `http://127.0.0.1:8080/sse`:\n\n```python\nfrom mcp.client.session import ClientSession\nfrom mcp.client.sse import sse_client\n# ...fastapi setup\n# ...\n\n\n@router.get(\"/mcp-list-tools\")\nasync def mcp_list_tools():\n async with sse_client(url=\"http://127.0.0.1:8080/sse\") as (read, write):\n async with ClientSession(read, write) as session:\n await session.initialize()\n\n tools = await session.list_tools()\n\n return tools\n\n\n@router.post(\"/mcp-call-tool\")\nasync def mcp_call_tool(tool_name: str, parameters: Dict[str, Any]):\n async with sse_client(url=\"http://127.0.0.1:8080/sse\") as (read, write):\n async with ClientSession(read, write) as session:\n await session.initialize()\n\n # # Call the fetch tool\n # result = await session.call_tool(\"fetch\", {\"url\": \"https://example.com\"})\n result = await session.call_tool(tool_name, parameters)\n\n return result\n```\n\n\nAdditionally, the `tests/test_mcp_list_tools.py` file can be run to test the `list_tools` method, for a sanity check. Just make sure the server is running.\n\n**Note:** More extensive documentation and usage is on the way.\n\n## Development\n\nTo run the project, use the following command:\n\n```bash\n>> poetry install --no-cache\n>> poetry shell\n>> poetry run mmcp create-mmcp --name my_project\n```\n\nTo build and run the project, use the following command:\n\n```bash\n>> cd path/to/your/mmcp\n>> python -m build\n>> pip install \"path/.../dist/mmcp-0.1.0.whl\"\n```\n\n## License\nThis project is licensed under the MIT License. See [LICENSE](LICENSE) for details.\n\n**NOTE**\n\nThis project is based on [create-python-server](https://github.com/modelcontextprotocol/create-python-server) by Anthropic, PBC.\n\nThis project is not affiliated with Anthropic, PBC., and does not reflect my views or opinions on the strengths or weaknesses of Anthropic's MCP.\n\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Create a low-code, SSE-transport-enabled Model Context Protocol server project from a template, packaged with Docker for easy deployment and orchestration.",
"version": "0.1.0",
"project_urls": {
"Homepage": "https://github.com/rscheiwe/mmcp",
"Repository": "https://github.com/rscheiwe/mmcp"
},
"split_keywords": [
"mcp",
" llm",
" automation",
" sse",
" server",
" template",
" low-code",
" microservice",
" api",
" generative-ai",
" ai"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "582415238abb146468e4344d34591165116d8db7db7e2b02784c7e83963b8cb3",
"md5": "b8484abfb21ee141db1b7c6257165632",
"sha256": "3493d8816eba32cc28cbaacd4be7a3f91cb3178c466c9e3bb44d38538eb98751"
},
"downloads": -1,
"filename": "mmcp-0.1.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "b8484abfb21ee141db1b7c6257165632",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 17623,
"upload_time": "2025-01-14T23:45:37",
"upload_time_iso_8601": "2025-01-14T23:45:37.674540Z",
"url": "https://files.pythonhosted.org/packages/58/24/15238abb146468e4344d34591165116d8db7db7e2b02784c7e83963b8cb3/mmcp-0.1.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "0bec6b890a6d068a6a1fcea0f68aba743fba63cc4dda34e4e3b3360b0c7323bb",
"md5": "c6649889b2dd43ebbd77d648e059eeb9",
"sha256": "495679c34080f2c8f7a024c6df559cb2f7795aa5f4adff1cfda80c5fe35a5bb2"
},
"downloads": -1,
"filename": "mmcp-0.1.0.tar.gz",
"has_sig": false,
"md5_digest": "c6649889b2dd43ebbd77d648e059eeb9",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 14737,
"upload_time": "2025-01-14T23:45:39",
"upload_time_iso_8601": "2025-01-14T23:45:39.095398Z",
"url": "https://files.pythonhosted.org/packages/0b/ec/6b890a6d068a6a1fcea0f68aba743fba63cc4dda34e4e3b3360b0c7323bb/mmcp-0.1.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-01-14 23:45:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "rscheiwe",
"github_project": "mmcp",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "mmcp"
}
JSON
